Wire live registration form (tuwaiq.edu.sa/form/rL7Bl3wq) into hero CTA, Step 1, and form notice
23afc76 verified | <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8" /> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0" /> | |
| <title>AISA-ArabicFC · Arabic Function Calling Shared Task · ArabicNLP 2026</title> | |
| <meta name="description" content="ArabicNLP 2026 shared task on Arabic function calling — 5 dialects, 8 domains, 27 tools. Co-located with EMNLP 2026, Budapest." /> | |
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| <style> | |
| :root { | |
| --teal: #57e3d8; | |
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| --purple: #4f29b7; | |
| --orange: #f4a664; | |
| --yellow: #ffdb5e; | |
| --blue: #4d96ff; | |
| --red: #ff8181; | |
| --lavender: #a380ff; | |
| --green: #80d883; | |
| --bg: #0f0e1a; | |
| --bg-2: #181628; | |
| --card: #1f1d33; | |
| --line: rgba(255,255,255,0.08); | |
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| * { margin: 0; padding: 0; box-sizing: border-box; } | |
| html { scroll-behavior: smooth; } | |
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| line-height: 1.65; | |
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| ::selection { background: var(--teal); color: var(--ink); } | |
| /* ── NAV ────────────────────────────────────────────────── */ | |
| nav { | |
| position: fixed; top: 0; left: 0; right: 0; | |
| z-index: 100; | |
| backdrop-filter: blur(16px); | |
| -webkit-backdrop-filter: blur(16px); | |
| background: rgba(15,14,26,0.72); | |
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| .nav-inner { | |
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| .nav-brand img { height: 44px; width: auto; } | |
| .nav-brand .badge { | |
| font-size: 10px; font-weight: 700; | |
| padding: 3px 8px; border-radius: 4px; | |
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| .nav-cta:hover { background: var(--paper) ; } | |
| @media (max-width: 1080px) { | |
| .nav-links a:not(.nav-cta) { display: none; } | |
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| /* ── HERO ───────────────────────────────────────────────── */ | |
| .hero { | |
| position: relative; | |
| min-height: 92vh; | |
| padding: 140px 32px 80px; | |
| display: flex; align-items: center; | |
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| background: | |
| radial-gradient(circle at 12% 18%, rgba(79,41,183,0.42) 0%, transparent 45%), | |
| radial-gradient(circle at 88% 78%, rgba(87,227,216,0.28) 0%, transparent 45%), | |
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| content: ''; | |
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| linear-gradient(rgba(87,227,216,0.04) 1px, transparent 1px), | |
| linear-gradient(90deg, rgba(87,227,216,0.04) 1px, transparent 1px); | |
| background-size: 60px 60px; | |
| mask-image: radial-gradient(ellipse at center, black 30%, transparent 75%); | |
| -webkit-mask-image: radial-gradient(ellipse at center, black 30%, transparent 75%); | |
| pointer-events: none; | |
| } | |
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| position: relative; z-index: 2; | |
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| padding: 6px 14px; | |
| background: rgba(87,227,216,0.12); | |
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| background: var(--teal); | |
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| color: var(--muted); | |
| margin-bottom: 16px; | |
| direction: rtl; | |
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| /* Arabic subtitle under each section heading */ | |
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| font-family: 'IBM Plex Sans Arabic', sans-serif; | |
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| text-decoration: none; | |
| transition: all 0.2s ease; | |
| border: 1px solid transparent; | |
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| .btn svg { width: 16px; height: 16px; } | |
| /* ── SECTION GENERIC ────────────────────────────────────── */ | |
| section { padding: 100px 32px; position: relative; } | |
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| display: inline-block; | |
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| color: var(--teal); | |
| margin-bottom: 16px; | |
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| margin-bottom: 18px; | |
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| .section-sub { | |
| font-size: 18px; color: var(--muted); | |
| max-width: 720px; margin-bottom: 60px; | |
| } | |
| /* ── OVERVIEW ───────────────────────────────────────────── */ | |
| .overview { background: var(--bg-2); } | |
| .overview-grid { | |
| display: grid; | |
| grid-template-columns: 1.4fr 1fr; | |
| gap: 60px; align-items: start; | |
| } | |
| @media (max-width: 880px) { .overview-grid { grid-template-columns: 1fr; gap: 40px; } } | |
| .overview p { font-size: 16px; color: var(--muted); margin-bottom: 16px; } | |
| .overview strong { color: var(--paper); font-weight: 600; } | |
| .overview-stats { | |
| display: grid; | |
| grid-template-columns: repeat(2, 1fr); | |
| gap: 16px; | |
| } | |
| .stat-mini { | |
| padding: 24px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 12px; | |
| transition: transform 0.2s ease, border-color 0.2s ease; | |
| } | |
| .stat-mini:hover { transform: translateY(-4px); } | |
| .stat-mini .num { | |
| font-size: 32px; font-weight: 800; | |
| letter-spacing: -0.02em; | |
| line-height: 1; | |
| margin-bottom: 6px; | |
| } | |
| .stat-mini.teal { border-color: rgba(87,227,216,0.3); } | |
| .stat-mini.teal .num { color: var(--teal); } | |
| .stat-mini.purple { border-color: rgba(163,128,255,0.3); } | |
| .stat-mini.purple .num { color: var(--lavender); } | |
| .stat-mini.orange { border-color: rgba(244,166,100,0.3); } | |
| .stat-mini.orange .num { color: var(--orange); } | |
| .stat-mini.yellow { border-color: rgba(255,219,94,0.3); } | |
| .stat-mini.yellow .num { color: var(--yellow); } | |
| .stat-mini .label { font-size: 13px; color: var(--muted); } | |
| /* ── AISA ───────────────────────────────────────────────── */ | |
| .aisa { | |
| position: relative; | |
| background: | |
| radial-gradient(circle at 85% 15%, rgba(79,41,183,0.25) 0%, transparent 50%), | |
| radial-gradient(circle at 15% 85%, rgba(87,227,216,0.15) 0%, transparent 50%), | |
| var(--bg); | |
| overflow: hidden; | |
| } | |
| .aisa::before { | |
| content: ''; | |
| position: absolute; inset: 0; | |
| background-image: | |
| linear-gradient(rgba(163,128,255,0.05) 1px, transparent 1px), | |
| linear-gradient(90deg, rgba(163,128,255,0.05) 1px, transparent 1px); | |
| background-size: 50px 50px; | |
| mask-image: radial-gradient(ellipse at center, black 20%, transparent 70%); | |
| -webkit-mask-image: radial-gradient(ellipse at center, black 20%, transparent 70%); | |
| pointer-events: none; | |
| } | |
| .aisa .container { position: relative; z-index: 2; } | |
| .aisa-tagline { | |
| font-size: 17px; | |
| color: var(--muted); | |
| margin-bottom: 28px; | |
| } | |
| .aisa-pillars { | |
| display: flex; flex-wrap: wrap; gap: 10px; | |
| margin-bottom: 36px; | |
| } | |
| .aisa-pillars .pillar { | |
| padding: 10px 18px; | |
| border: 1px solid var(--line); | |
| border-radius: 99px; | |
| font-size: 13.5px; | |
| font-weight: 600; | |
| color: var(--paper); | |
| background: rgba(255,255,255,0.03); | |
| transition: all 0.2s ease; | |
| } | |
| .aisa-pillars .pillar:nth-child(1) { border-color: rgba(87,227,216,0.4); color: var(--teal); } | |
| .aisa-pillars .pillar:nth-child(2) { border-color: rgba(163,128,255,0.4); color: var(--lavender); } | |
| .aisa-pillars .pillar:nth-child(3) { border-color: rgba(244,166,100,0.4); color: var(--orange); } | |
| .aisa-pillars .pillar:nth-child(4) { border-color: rgba(128,216,131,0.4); color: var(--green); } | |
| .aisa-cta { display: flex; gap: 12px; flex-wrap: wrap; margin-bottom: 56px; } | |
| .aisa-content { | |
| display: grid; | |
| grid-template-columns: 1fr 1fr; | |
| gap: 24px; | |
| margin-bottom: 36px; | |
| } | |
| @media (max-width: 880px) { .aisa-content { grid-template-columns: 1fr; } } | |
| .aisa-card { | |
| padding: 32px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 14px; | |
| position: relative; | |
| } | |
| .aisa-card .card-num { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 11px; | |
| font-weight: 600; | |
| color: var(--teal); | |
| letter-spacing: 0.1em; | |
| margin-bottom: 12px; | |
| display: block; | |
| } | |
| .aisa-card:nth-child(2) .card-num { color: var(--lavender); } | |
| .aisa-card h3 { | |
| font-size: 22px; | |
| font-weight: 700; | |
| margin-bottom: 14px; | |
| letter-spacing: -0.015em; | |
| } | |
| .aisa-card p { | |
| font-size: 15px; | |
| color: var(--muted); | |
| line-height: 1.7; | |
| } | |
| .aisa-citation { | |
| padding: 22px 26px; | |
| background: rgba(163,128,255,0.06); | |
| border-left: 3px solid var(--lavender); | |
| border-radius: 6px; | |
| font-size: 14px; | |
| color: var(--muted); | |
| line-height: 1.7; | |
| } | |
| .aisa-citation strong { color: var(--paper); font-weight: 600; } | |
| .aisa-citation a { | |
| color: var(--teal); | |
| text-decoration: none; | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 13px; | |
| word-break: break-all; | |
| } | |
| .aisa-citation a:hover { text-decoration: underline; } | |
| /* ── TRACKS ─────────────────────────────────────────────── */ | |
| .tracks-grid { | |
| display: grid; | |
| grid-template-columns: repeat(3, 1fr); | |
| gap: 24px; | |
| } | |
| @media (max-width: 980px) { .tracks-grid { grid-template-columns: 1fr; } } | |
| .track-card { | |
| position: relative; | |
| padding: 36px 32px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 16px; | |
| overflow: hidden; | |
| transition: transform 0.25s ease, border-color 0.25s ease; | |
| } | |
| .track-card:hover { transform: translateY(-6px); } | |
| .track-card::before { | |
| content: ''; | |
| position: absolute; top: 0; left: 0; right: 0; height: 4px; | |
| } | |
| .track-card.a::before { background: linear-gradient(90deg, var(--teal), var(--blue)); } | |
| .track-card.b::before { background: linear-gradient(90deg, var(--lavender), var(--purple)); } | |
| .track-card.c::before { background: linear-gradient(90deg, var(--orange), var(--yellow)); } | |
| .track-card.a:hover { border-color: rgba(87,227,216,0.4); } | |
| .track-card.b:hover { border-color: rgba(163,128,255,0.4); } | |
| .track-card.c:hover { border-color: rgba(244,166,100,0.4); } | |
| .track-id { | |
| display: inline-block; | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 11px; font-weight: 600; | |
| padding: 4px 10px; | |
| border-radius: 4px; | |
| margin-bottom: 18px; | |
| letter-spacing: 0.06em; | |
| } | |
| .track-card.a .track-id { background: rgba(87,227,216,0.15); color: var(--teal); } | |
| .track-card.b .track-id { background: rgba(163,128,255,0.15); color: var(--lavender); } | |
| .track-card.c .track-id { background: rgba(244,166,100,0.15); color: var(--orange); } | |
| .track-card h3 { | |
| font-size: 22px; font-weight: 700; | |
| margin-bottom: 14px; | |
| letter-spacing: -0.015em; | |
| } | |
| .track-card p { font-size: 14.5px; color: var(--muted); margin-bottom: 18px; } | |
| .track-card ul { list-style: none; } | |
| .track-card li { | |
| font-size: 13.5px; color: var(--muted); | |
| padding-left: 22px; position: relative; | |
| margin-bottom: 8px; | |
| } | |
| .track-card li::before { | |
| content: '→'; | |
| position: absolute; left: 0; | |
| color: var(--teal); font-weight: 700; | |
| } | |
| .track-card.b li::before { color: var(--lavender); } | |
| .track-card.c li::before { color: var(--orange); } | |
| /* ── DATA ───────────────────────────────────────────────── */ | |
| .data { background: var(--bg-2); } | |
| .data-grid { | |
| display: grid; | |
| grid-template-columns: 1fr 1fr; | |
| gap: 40px; align-items: start; | |
| } | |
| @media (max-width: 880px) { .data-grid { grid-template-columns: 1fr; } } | |
| table.data-table { | |
| width: 100%; | |
| border-collapse: collapse; | |
| background: var(--card); | |
| border-radius: 12px; | |
| overflow: hidden; | |
| border: 1px solid var(--line); | |
| } | |
| table.data-table th, | |
| table.data-table td { | |
| padding: 14px 18px; | |
| text-align: left; | |
| font-size: 14px; | |
| border-bottom: 1px solid var(--line); | |
| } | |
| table.data-table th { | |
| background: rgba(255,255,255,0.03); | |
| font-weight: 600; | |
| color: var(--paper); | |
| font-size: 12px; | |
| letter-spacing: 0.04em; | |
| text-transform: uppercase; | |
| } | |
| table.data-table td { color: var(--muted); } | |
| table.data-table td:first-child { color: var(--paper); font-weight: 500; } | |
| table.data-table tr:last-child td { border-bottom: none; } | |
| .data-card { | |
| padding: 32px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 14px; | |
| } | |
| .data-card h3 { | |
| font-size: 18px; font-weight: 700; margin-bottom: 18px; | |
| display: flex; align-items: center; gap: 10px; | |
| } | |
| .data-card h3 .icon { | |
| width: 28px; height: 28px; border-radius: 7px; | |
| background: rgba(87,227,216,0.15); | |
| display: flex; align-items: center; justify-content: center; | |
| color: var(--teal); font-size: 14px; | |
| } | |
| .code-block { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 12.5px; | |
| background: var(--bg); | |
| border: 1px solid var(--line); | |
| border-radius: 8px; | |
| padding: 14px 16px; | |
| color: var(--paper); | |
| overflow-x: auto; | |
| margin-top: 12px; | |
| line-height: 1.7; | |
| } | |
| .code-block .c { color: var(--teal); } | |
| .code-block .k { color: var(--lavender); } | |
| .code-block .s { color: var(--orange); } | |
| .domains-grid { | |
| display: grid; | |
| grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); | |
| gap: 14px; | |
| margin-top: 40px; | |
| } | |
| .domain-tag { | |
| padding: 14px 18px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 10px; | |
| font-size: 14px; | |
| transition: all 0.2s ease; | |
| } | |
| .domain-tag:hover { border-color: var(--teal); transform: translateY(-2px); } | |
| .domain-tag .d-name { font-weight: 600; color: var(--paper); margin-bottom: 2px; } | |
| .domain-tag .d-tools { font-size: 11.5px; color: var(--muted); } | |
| /* ── METRICS ────────────────────────────────────────────── */ | |
| .formula-stack { | |
| display: grid; | |
| grid-template-columns: 1fr 1fr; | |
| gap: 16px; | |
| margin-bottom: 32px; | |
| } | |
| @media (max-width: 760px) { .formula-stack { grid-template-columns: 1fr; } } | |
| .formula-box { | |
| padding: 28px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 14px; | |
| text-align: center; | |
| overflow-x: auto; | |
| position: relative; | |
| } | |
| .formula-label { | |
| position: absolute; top: 14px; left: 18px; | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 11px; font-weight: 700; | |
| color: var(--teal); | |
| letter-spacing: 0.1em; | |
| } | |
| .formula-stack .formula-box:nth-child(2) .formula-label { color: var(--lavender); } | |
| .formula-box .formula { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: clamp(14px, 1.6vw, 20px); | |
| font-weight: 500; | |
| color: var(--paper); | |
| white-space: nowrap; | |
| } | |
| .formula .w { color: var(--teal); } | |
| .formula .m { color: var(--lavender); } | |
| .metrics-grid { | |
| display: grid; | |
| grid-template-columns: repeat(2, 1fr); | |
| gap: 16px; | |
| } | |
| @media (max-width: 720px) { .metrics-grid { grid-template-columns: 1fr; } } | |
| .metric-card { | |
| padding: 24px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 12px; | |
| } | |
| .metric-card .m-name { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 14px; font-weight: 600; | |
| color: var(--teal); | |
| margin-bottom: 8px; | |
| } | |
| .metric-card .m-desc { font-size: 14px; color: var(--muted); } | |
| .metric-card.weight { position: relative; } | |
| .metric-card .weight-pill { | |
| position: absolute; top: 16px; right: 16px; | |
| font-size: 11px; font-weight: 700; | |
| padding: 3px 8px; | |
| background: rgba(255,219,94,0.15); | |
| color: var(--yellow); | |
| border-radius: 4px; | |
| } | |
| /* ── BASELINES ──────────────────────────────────────────── */ | |
| .baselines { background: var(--bg-2); } | |
| .baseline-table-wrap { | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 14px; | |
| overflow: hidden; | |
| margin-bottom: 40px; | |
| } | |
| table.baseline-table { | |
| width: 100%; | |
| border-collapse: collapse; | |
| } | |
| table.baseline-table th, | |
| table.baseline-table td { | |
| padding: 16px 22px; | |
| text-align: left; | |
| border-bottom: 1px solid var(--line); | |
| font-size: 14px; | |
| } | |
| table.baseline-table th { | |
| background: rgba(255,255,255,0.03); | |
| font-size: 11px; font-weight: 700; | |
| letter-spacing: 0.08em; text-transform: uppercase; | |
| color: var(--paper); | |
| } | |
| table.baseline-table .num-col { | |
| text-align: right; | |
| font-family: 'JetBrains Mono', monospace; | |
| font-variant-numeric: tabular-nums; | |
| } | |
| table.baseline-table .highlight-col { | |
| background: rgba(244,166,100,0.06); | |
| color: var(--orange); | |
| } | |
| table.baseline-table th.highlight-col { | |
| background: rgba(244,166,100,0.12); | |
| color: var(--orange); | |
| } | |
| table.baseline-table tbody tr:last-child td { border-bottom: none; } | |
| table.baseline-table tr.best td { background: rgba(87,227,216,0.04); } | |
| table.baseline-table tr.best td strong { color: var(--teal); } | |
| table.baseline-table tr.best .highlight-col strong { color: var(--orange); } | |
| table.baseline-table tr.dim td { color: var(--muted); opacity: 0.7; } | |
| table.baseline-table .sys-name { | |
| font-weight: 700; | |
| color: var(--paper); | |
| margin-bottom: 2px; | |
| } | |
| table.baseline-table .sys-desc { | |
| font-size: 12px; | |
| color: var(--muted); | |
| } | |
| .baseline-footnote { | |
| padding: 14px 22px; | |
| background: rgba(163,128,255,0.05); | |
| border-top: 1px solid var(--line); | |
| font-size: 13px; | |
| color: var(--muted); | |
| } | |
| .baseline-footnote strong { color: var(--lavender); font-family: 'JetBrains Mono', monospace; } | |
| .findings-grid { | |
| display: grid; | |
| grid-template-columns: repeat(3, 1fr); | |
| gap: 20px; | |
| } | |
| @media (max-width: 880px) { .findings-grid { grid-template-columns: 1fr; } } | |
| .finding { | |
| padding: 28px 24px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 14px; | |
| } | |
| .finding-icon { | |
| width: 44px; height: 44px; border-radius: 10px; | |
| display: flex; align-items: center; justify-content: center; | |
| font-size: 22px; margin-bottom: 16px; | |
| } | |
| .finding h3 { | |
| font-size: 16px; font-weight: 700; | |
| margin-bottom: 10px; | |
| letter-spacing: -0.01em; | |
| } | |
| .finding p { font-size: 14px; color: var(--muted); line-height: 1.65; } | |
| .finding strong { color: var(--paper); font-weight: 600; } | |
| /* ── PRIZES ─────────────────────────────────────────────── */ | |
| .prizes { | |
| position: relative; | |
| overflow: hidden; | |
| } | |
| .prizes::before { | |
| content: ''; | |
| position: absolute; | |
| top: 30%; | |
| left: 50%; | |
| transform: translate(-50%, -50%); | |
| width: 700px; | |
| height: 700px; | |
| background: radial-gradient(circle, rgba(255,219,94,0.08) 0%, transparent 60%); | |
| pointer-events: none; | |
| } | |
| .prize-grid { | |
| display: grid; | |
| grid-template-columns: repeat(3, 1fr); | |
| gap: 20px; | |
| align-items: end; | |
| margin-top: 24px; | |
| position: relative; | |
| z-index: 2; | |
| } | |
| @media (max-width: 880px) { | |
| .prize-grid { grid-template-columns: 1fr; align-items: stretch; } | |
| } | |
| .prize-card { | |
| position: relative; | |
| padding: 40px 28px 36px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 16px; | |
| text-align: center; | |
| transition: transform 0.25s ease; | |
| overflow: hidden; | |
| } | |
| .prize-card::before { | |
| content: ''; | |
| position: absolute; | |
| top: 0; left: 0; right: 0; height: 4px; | |
| } | |
| .prize-card.first { | |
| padding-top: 56px; | |
| padding-bottom: 52px; | |
| transform: translateY(-20px); | |
| border-color: rgba(255,219,94,0.5); | |
| box-shadow: 0 16px 56px rgba(255,219,94,0.18); | |
| background: linear-gradient(180deg, rgba(255,219,94,0.06) 0%, var(--card) 60%); | |
| } | |
| .prize-card.first::before { background: linear-gradient(90deg, #f4a664, #ffdb5e, #f4a664); } | |
| .prize-card.second::before { background: linear-gradient(90deg, #a380ff, #cdc5e0); } | |
| .prize-card.third::before { background: linear-gradient(90deg, #f4a664, #c97f3e); } | |
| .prize-card:hover { transform: translateY(-26px); } | |
| .prize-card.second:hover, | |
| .prize-card.third:hover { transform: translateY(-6px); } | |
| .prize-medal { | |
| font-size: 56px; | |
| line-height: 1; | |
| margin-bottom: 14px; | |
| filter: drop-shadow(0 4px 14px rgba(0,0,0,0.25)); | |
| } | |
| .prize-card.first .prize-medal { font-size: 68px; } | |
| .prize-rank { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 11px; | |
| font-weight: 700; | |
| letter-spacing: 0.18em; | |
| text-transform: uppercase; | |
| color: var(--muted); | |
| margin-bottom: 18px; | |
| } | |
| .prize-amount { | |
| font-size: 64px; | |
| font-weight: 900; | |
| letter-spacing: -0.04em; | |
| line-height: 1; | |
| margin-bottom: 10px; | |
| } | |
| .prize-card.first .prize-amount { font-size: 76px; color: var(--yellow); } | |
| .prize-card.second .prize-amount { color: var(--lavender); } | |
| .prize-card.third .prize-amount { color: var(--orange); } | |
| .prize-label { | |
| font-size: 13px; | |
| color: var(--muted); | |
| letter-spacing: 0.04em; | |
| text-transform: uppercase; | |
| } | |
| .prize-total { | |
| margin-top: 36px; | |
| padding: 22px 28px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 12px; | |
| display: flex; | |
| align-items: center; | |
| justify-content: space-between; | |
| flex-wrap: wrap; | |
| gap: 16px; | |
| } | |
| .prize-total .pt-amount { | |
| font-size: 26px; | |
| font-weight: 800; | |
| color: var(--yellow); | |
| letter-spacing: -0.02em; | |
| } | |
| .prize-total .pt-text { | |
| font-size: 14px; | |
| color: var(--muted); | |
| max-width: 580px; | |
| } | |
| .prize-total .pt-text strong { color: var(--paper); font-weight: 600; } | |
| /* ── PARTICIPATE ────────────────────────────────────────── */ | |
| .participate { background: var(--bg-2); } | |
| .steps { | |
| display: grid; | |
| grid-template-columns: repeat(4, 1fr); | |
| gap: 20px; | |
| } | |
| @media (max-width: 980px) { .steps { grid-template-columns: repeat(2, 1fr); } } | |
| @media (max-width: 540px) { .steps { grid-template-columns: 1fr; } } | |
| .step { | |
| padding: 28px 24px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 14px; | |
| position: relative; | |
| } | |
| .step-num { | |
| display: inline-flex; | |
| align-items: center; justify-content: center; | |
| width: 38px; height: 38px; | |
| border-radius: 10px; | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 16px; font-weight: 700; | |
| color: var(--ink); | |
| margin-bottom: 18px; | |
| } | |
| .step:nth-child(1) .step-num { background: var(--teal); } | |
| .step:nth-child(2) .step-num { background: var(--lavender); } | |
| .step:nth-child(3) .step-num { background: var(--orange); } | |
| .step:nth-child(4) .step-num { background: var(--green); } | |
| .step h3 { font-size: 17px; font-weight: 700; margin-bottom: 10px; } | |
| .step p { font-size: 14px; color: var(--muted); line-height: 1.6; } | |
| .step a { color: var(--teal); text-decoration: none; font-weight: 500; } | |
| .step a:hover { text-decoration: underline; } | |
| .form-notice { | |
| margin-top: 36px; | |
| padding: 22px 28px; | |
| background: linear-gradient(135deg, rgba(244,166,100,0.12), rgba(255,219,94,0.08)); | |
| border: 1px solid rgba(244,166,100,0.35); | |
| border-radius: 12px; | |
| display: flex; align-items: center; gap: 18px; | |
| flex-wrap: wrap; | |
| } | |
| .form-notice .fn-icon { | |
| flex-shrink: 0; | |
| width: 44px; height: 44px; | |
| border-radius: 10px; | |
| background: rgba(244,166,100,0.2); | |
| display: flex; align-items: center; justify-content: center; | |
| color: var(--orange); | |
| font-size: 20px; | |
| } | |
| .form-notice .fn-text { flex: 1; min-width: 260px; } | |
| .form-notice .fn-title { | |
| font-size: 15px; font-weight: 700; color: var(--paper); | |
| margin-bottom: 4px; | |
| } | |
| .form-notice .fn-desc { | |
| font-size: 13.5px; color: var(--muted); | |
| } | |
| .form-notice .fn-pill { | |
| display: inline-flex; align-items: center; gap: 6px; | |
| padding: 6px 14px; | |
| background: var(--orange); | |
| color: var(--ink); | |
| font-size: 12px; font-weight: 700; | |
| border-radius: 99px; | |
| letter-spacing: 0.04em; text-transform: uppercase; | |
| } | |
| .form-notice .fn-pill .dot { | |
| width: 6px; height: 6px; border-radius: 50%; | |
| background: var(--ink); | |
| animation: pulse 2s ease-in-out infinite; | |
| } | |
| .cite-notice { | |
| margin-top: 22px; | |
| padding: 26px 30px; | |
| background: rgba(163,128,255,0.06); | |
| border: 1px solid rgba(163,128,255,0.3); | |
| border-left: 3px solid var(--lavender); | |
| border-radius: 12px; | |
| } | |
| .cite-notice .cn-head { | |
| display: flex; align-items: center; gap: 10px; | |
| color: var(--lavender); | |
| font-weight: 700; font-size: 15px; | |
| margin-bottom: 10px; | |
| } | |
| .cite-notice p { | |
| font-size: 14px; color: var(--muted); | |
| margin-bottom: 14px; | |
| } | |
| .cite-notice p a { color: var(--teal); text-decoration: none; font-weight: 600; } | |
| .cite-notice p a:hover { text-decoration: underline; } | |
| .cite-notice ul { list-style: none; } | |
| .cite-notice li { | |
| font-size: 13.5px; color: var(--muted); | |
| padding: 8px 0 8px 22px; | |
| position: relative; | |
| line-height: 1.6; | |
| } | |
| .cite-notice li::before { | |
| content: '→'; | |
| position: absolute; left: 0; top: 8px; | |
| color: var(--lavender); font-weight: 700; | |
| } | |
| .cite-notice li strong { color: var(--paper); font-weight: 600; } | |
| .cite-notice li em { color: var(--paper); font-style: italic; } | |
| /* ── TIMELINE ───────────────────────────────────────────── */ | |
| .timeline { | |
| position: relative; | |
| padding-left: 32px; | |
| margin-top: 20px; | |
| } | |
| .timeline::before { | |
| content: ''; | |
| position: absolute; left: 11px; top: 8px; bottom: 8px; | |
| width: 2px; | |
| background: linear-gradient(180deg, var(--teal), var(--lavender), var(--orange)); | |
| } | |
| .tl-item { | |
| position: relative; | |
| padding-bottom: 28px; | |
| } | |
| .tl-item:last-child { padding-bottom: 0; } | |
| .tl-item::before { | |
| content: ''; | |
| position: absolute; | |
| left: -28px; top: 6px; | |
| width: 14px; height: 14px; | |
| border-radius: 50%; | |
| background: var(--bg); | |
| border: 2px solid var(--teal); | |
| } | |
| .tl-item.mandatory::before { border-color: var(--red); background: var(--red); } | |
| .tl-item.passed::before { background: var(--teal); } | |
| .tl-date { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 13px; font-weight: 600; | |
| color: var(--teal); | |
| margin-bottom: 4px; | |
| } | |
| .tl-item.mandatory .tl-date { color: var(--red); } | |
| .tl-title { font-size: 16px; font-weight: 600; color: var(--paper); margin-bottom: 4px; } | |
| .tl-desc { font-size: 13.5px; color: var(--muted); } | |
| .tl-tag { | |
| display: inline-block; | |
| margin-left: 10px; | |
| font-size: 10px; font-weight: 700; | |
| padding: 2px 8px; border-radius: 4px; | |
| letter-spacing: 0.05em; text-transform: uppercase; | |
| } | |
| .tag-rec { background: rgba(87,227,216,0.15); color: var(--teal); } | |
| .tag-man { background: rgba(255,129,129,0.15); color: var(--red); } | |
| .tag-conf { background: rgba(163,128,255,0.15); color: var(--lavender); } | |
| /* ── RESOURCES ──────────────────────────────────────────── */ | |
| .resources { background: var(--bg-2); } | |
| .res-group { | |
| margin-bottom: 56px; | |
| } | |
| .res-group:last-child { margin-bottom: 0; } | |
| .res-group-head { | |
| display: flex; align-items: flex-start; gap: 16px; | |
| margin-bottom: 22px; | |
| padding-bottom: 18px; | |
| border-bottom: 1px solid var(--line); | |
| } | |
| .res-group .rg-num { | |
| flex-shrink: 0; | |
| width: 42px; height: 42px; | |
| border-radius: 10px; | |
| display: flex; align-items: center; justify-content: center; | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 14px; font-weight: 700; | |
| color: var(--ink); | |
| } | |
| .res-group:nth-of-type(1) .rg-num { background: var(--teal); } | |
| .res-group:nth-of-type(2) .rg-num { background: var(--lavender); } | |
| .res-group:nth-of-type(3) .rg-num { background: var(--orange); } | |
| .rg-title { | |
| font-size: 22px; | |
| font-weight: 700; | |
| color: var(--paper); | |
| letter-spacing: -0.015em; | |
| margin-bottom: 4px; | |
| } | |
| .rg-desc { | |
| font-size: 14.5px; | |
| color: var(--muted); | |
| } | |
| .res-grid { | |
| display: grid; | |
| grid-template-columns: repeat(auto-fit, minmax(260px, 1fr)); | |
| gap: 18px; | |
| } | |
| .res-card { | |
| display: block; | |
| padding: 26px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 14px; | |
| text-decoration: none; | |
| color: inherit; | |
| transition: all 0.2s ease; | |
| } | |
| .res-card:hover { | |
| transform: translateY(-4px); | |
| border-color: var(--teal); | |
| } | |
| /* Build-group action cards */ | |
| .build-grid { | |
| display: grid; | |
| grid-template-columns: repeat(3, 1fr); | |
| gap: 18px; | |
| } | |
| @media (max-width: 900px) { .build-grid { grid-template-columns: 1fr; } } | |
| .build-card { | |
| position: relative; | |
| display: flex; | |
| flex-direction: column; | |
| align-items: flex-start; | |
| padding: 30px 28px 26px; | |
| background: var(--card); | |
| border: 1px solid var(--line); | |
| border-radius: 14px; | |
| text-decoration: none; | |
| color: inherit; | |
| transition: transform 0.2s ease, border-color 0.2s ease; | |
| overflow: hidden; | |
| } | |
| .build-card:hover { | |
| transform: translateY(-4px); | |
| border-color: rgba(87,227,216,0.4); | |
| } | |
| .build-card.disabled { | |
| cursor: default; | |
| opacity: 0.88; | |
| } | |
| .build-card.disabled:hover { | |
| transform: none; | |
| border-color: var(--line); | |
| } | |
| .bc-step { | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 11px; | |
| font-weight: 700; | |
| letter-spacing: 0.12em; | |
| text-transform: uppercase; | |
| color: var(--muted); | |
| margin-bottom: 18px; | |
| } | |
| .bc-icon-wrap { | |
| width: 56px; height: 56px; | |
| border-radius: 12px; | |
| display: flex; align-items: center; justify-content: center; | |
| font-size: 26px; | |
| margin-bottom: 18px; | |
| } | |
| .teal-bg { background: rgba(87,227,216,0.15); } | |
| .lavender-bg { background: rgba(163,128,255,0.15); } | |
| .orange-bg { background: rgba(244,166,100,0.15); } | |
| .teal-fg { color: var(--teal); } | |
| .lavender-fg { color: var(--lavender); } | |
| .orange-fg { color: var(--orange); } | |
| .build-card h3 { | |
| font-size: 20px; | |
| font-weight: 700; | |
| letter-spacing: -0.015em; | |
| margin-bottom: 10px; | |
| color: var(--paper); | |
| } | |
| .build-card p { | |
| font-size: 14.5px; | |
| line-height: 1.6; | |
| color: var(--muted); | |
| margin-bottom: 20px; | |
| flex-grow: 1; | |
| } | |
| .build-card p strong { color: var(--paper); font-weight: 600; } | |
| .bc-cta { | |
| font-size: 14px; | |
| font-weight: 700; | |
| letter-spacing: 0.01em; | |
| } | |
| .res-card .res-icon { | |
| width: 44px; height: 44px; border-radius: 10px; | |
| display: flex; align-items: center; justify-content: center; | |
| font-size: 22px; | |
| margin-bottom: 16px; | |
| } | |
| .res-card .res-title { | |
| font-size: 16px; font-weight: 700; | |
| margin-bottom: 6px; | |
| display: flex; align-items: center; gap: 8px; | |
| } | |
| .res-card .res-title svg { width: 14px; height: 14px; color: var(--muted); } | |
| .res-card .res-desc { font-size: 13.5px; color: var(--muted); } | |
| .res-card .res-link { | |
| display: block; | |
| margin-top: 12px; | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 12px; | |
| color: var(--teal); | |
| word-break: break-all; | |
| } | |
| .baseline-results { | |
| display: grid; | |
| grid-template-columns: repeat(4, 1fr); | |
| gap: 8px; | |
| margin-top: 14px; | |
| padding: 14px; | |
| background: rgba(163,128,255,0.06); | |
| border: 1px solid rgba(163,128,255,0.2); | |
| border-radius: 8px; | |
| } | |
| .baseline-results .br-item { | |
| text-align: center; | |
| } | |
| .baseline-results .br-num { | |
| display: block; | |
| font-family: 'JetBrains Mono', monospace; | |
| font-size: 15px; | |
| font-weight: 700; | |
| color: var(--lavender); | |
| line-height: 1.1; | |
| } | |
| .baseline-results .br-lab { | |
| display: block; | |
| font-size: 10px; | |
| color: var(--muted); | |
| margin-top: 4px; | |
| letter-spacing: 0.04em; | |
| text-transform: uppercase; | |
| } | |
| .baseline-results .br-item.highlight { | |
| background: rgba(244,166,100,0.12); | |
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| /* ── ORGANIZERS ─────────────────────────────────────────── */ | |
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| /* ── FOOTER ─────────────────────────────────────────────── */ | |
| footer { | |
| padding: 60px 32px 40px; | |
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| grid-template-columns: 2fr 1fr 1fr 1fr; | |
| gap: 40px; | |
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| @media (max-width: 880px) { | |
| .footer-inner { grid-template-columns: 1fr 1fr; } | |
| } | |
| .footer-brand img { height: 56px; margin-bottom: 18px; } | |
| .footer-brand p { font-size: 13px; color: var(--muted); max-width: 320px; } | |
| .footer-col h4 { | |
| font-size: 12px; font-weight: 700; | |
| letter-spacing: 0.1em; text-transform: uppercase; | |
| color: var(--paper); margin-bottom: 14px; | |
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| max-width: 1240px; margin: 40px auto 0; | |
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| border-top: 1px solid var(--line); | |
| display: flex; justify-content: space-between; flex-wrap: wrap; gap: 12px; | |
| font-size: 12px; color: var(--muted); | |
| } | |
| /* ── UTILS ──────────────────────────────────────────────── */ | |
| .glow { text-shadow: 0 0 30px rgba(87,227,216,0.5); } | |
| </style> | |
| </head> | |
| <body> | |
| <nav> | |
| <div class="nav-inner"> | |
| <div class="nav-brand"> | |
| <img src="assets/tuwaiq-logo.png" alt="Tuwaiq Academy" /> | |
| <span class="badge">ArabicNLP 2026</span> | |
| </div> | |
| <div class="nav-links"> | |
| <a href="#overview">Overview</a> | |
| <a href="#tracks">Tracks</a> | |
| <a href="#data">Data</a> | |
| <a href="#prizes">Prizes</a> | |
| <a href="#participate">Participate</a> | |
| <a href="https://huggingface.co/spaces/TuwaiqAcademy/AISA-ArabicFC-SharedTask-Leaderboard" target="_blank">Leaderboard ↗</a> | |
| <a href="https://huggingface.co/datasets/TuwaiqAcademy/AISA-ArabicFC" target="_blank" class="nav-cta">Get the Data →</a> | |
| </div> | |
| </div> | |
| </nav> | |
| <header class="hero"> | |
| <div class="hero-inner"> | |
| <div class="pill"><span class="dot"></span> Accepted Shared Task · ArabicNLP 2026</div> | |
| <div class="hero-arabic">مهمة مشتركة لاستدعاء الدوال العربية في أنظمة الذكاء الاصطناعي التوكيلي</div> | |
| <h1 class="hero-title">AISA-ArabicFC</h1> | |
| <p class="hero-sub"> | |
| Arabic Function Calling for Agentic AI Systems — the first shared task benchmarking | |
| tool-use in Arabic across <strong style="color:var(--paper);">five dialects, eight real-world domains,</strong> | |
| and <strong style="color:var(--paper);">27 structured tools.</strong> | |
| </p> | |
| <div class="hero-meta"> | |
| <span class="chip"> | |
| <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><rect x="3" y="4" width="18" height="18" rx="2"/><path d="M16 2v4M8 2v4M3 10h18"/></svg> | |
| Oct 24–29, 2026 | |
| </span> | |
| <span class="chip"> | |
| <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M12 2C8 6 8 12 12 22C16 12 16 6 12 2Z"/><circle cx="12" cy="10" r="3"/></svg> | |
| Budapest, Hungary | |
| </span> | |
| <span class="chip"> | |
| <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M21 16V8a2 2 0 00-1-1.73l-7-4a2 2 0 00-2 0l-7 4A2 2 0 003 8v8a2 2 0 001 1.73l7 4a2 2 0 002 0l7-4A2 2 0 0021 16z"/></svg> | |
| Co-located with EMNLP 2026 | |
| </span> | |
| <span class="chip"> | |
| <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><circle cx="12" cy="12" r="10"/><path d="M2 12h20M12 2a15 15 0 010 20M12 2a15 15 0 000 20"/></svg> | |
| Open to teams worldwide | |
| </span> | |
| <span class="chip"> | |
| <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M4 19.5A2.5 2.5 0 016.5 17H20"/><path d="M6.5 2H20v20H6.5A2.5 2.5 0 014 19.5v-15A2.5 2.5 0 016.5 2z"/></svg> | |
| Arabic NLP Conference | |
| </span> | |
| </div> | |
| <div class="cta-row"> | |
| <a href="https://tuwaiq.edu.sa/form/rL7Bl3wq" target="_blank" class="btn btn-primary"> | |
| <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M14 2H6a2 2 0 00-2 2v16a2 2 0 002 2h12a2 2 0 002-2V8z"/><path d="M14 2v6h6M9 15l2 2 4-4"/></svg> | |
| Register Your Team | |
| </a> | |
| <a href="https://huggingface.co/datasets/TuwaiqAcademy/AISA-ArabicFC" target="_blank" class="btn btn-secondary"> | |
| <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M21 15v4a2 2 0 01-2 2H5a2 2 0 01-2-2v-4M7 10l5 5 5-5M12 15V3"/></svg> | |
| Get the Data | |
| </a> | |
| <a href="#participate" class="btn btn-secondary"> | |
| How to Participate | |
| <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M5 12h14M12 5l7 7-7 7"/></svg> | |
| </a> | |
| </div> | |
| </div> | |
| </header> | |
| <!-- ── OVERVIEW ──────────────────────────────────────────── --> | |
| <section id="overview" class="overview"> | |
| <div class="container"> | |
| <div class="overview-grid"> | |
| <div> | |
| <span class="section-tag">The Challenge</span> | |
| <h2>Teach machines to act in Arabic.</h2> | |
| <div class="ar-heading" lang="ar">علّم الآلات أن تتصرف بالعربية.</div> | |
| <p> | |
| Function calling — the bridge between language models and the real world — has exploded in English. | |
| Models can book flights, query databases, and chain tools into autonomous agents. | |
| For Arabic, with its rich dialectal variation and morphological complexity, <strong>this capability barely exists.</strong> | |
| </p> | |
| <p> | |
| <strong>AISA-ArabicFC</strong> closes that gap. Given an Arabic query in any of five dialects, your system must | |
| decide whether a tool call is needed, choose the right function from a candidate set, | |
| and extract structured arguments — optionally producing an Arabic reasoning trace. | |
| </p> | |
| <p> | |
| A user in Cairo says <em style="color:var(--teal);">"عايز أحجز دكتور"</em>. | |
| A user in Riyadh says <em style="color:var(--teal);">"أبي أحجز موعد عند الدكتور"</em>. | |
| Same intent. Same tool. Your model has to know. | |
| </p> | |
| </div> | |
| <div class="overview-stats"> | |
| <div class="stat-mini teal"><div class="num">12,125</div><div class="label">total samples</div></div> | |
| <div class="stat-mini purple"><div class="num">5</div><div class="label">Arabic dialects</div></div> | |
| <div class="stat-mini orange"><div class="num">27</div><div class="label">structured tools</div></div> | |
| <div class="stat-mini yellow"><div class="num">8</div><div class="label">service domains</div></div> | |
| </div> | |
| </div> | |
| </div> | |
| </section> | |
| <!-- ── AISA ──────────────────────────────────────────────── --> | |
| <section id="aisa" class="aisa"> | |
| <div class="container"> | |
| <span class="section-tag">Powered by AISA</span> | |
| <h2>A unified reference architecture for agentic AI systems.</h2> | |
| <div class="ar-heading" lang="ar">بنية مرجعية موحّدة لأنظمة الذكاء الاصطناعي التوكيلي.</div> | |
| <p class="aisa-tagline">A reference architecture proposed by <strong style="color:var(--paper);">Tuwaiq Academy</strong> — the foundation behind AISA-ArabicFC.</p> | |
| <div class="aisa-pillars"> | |
| <span class="pillar">Design</span> | |
| <span class="pillar">Evaluation</span> | |
| <span class="pillar">Governance</span> | |
| <span class="pillar">Deployment</span> | |
| </div> | |
| <div class="aisa-cta"> | |
| <a href="https://doi.org/10.5281/zenodo.18161880" target="_blank" class="btn btn-primary"> | |
| <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M14 2H6a2 2 0 00-2 2v16a2 2 0 002 2h12a2 2 0 002-2V8z"/><path d="M14 2v6h6M16 13H8M16 17H8M10 9H8"/></svg> | |
| Read the Paper | |
| </a> | |
| <a href="https://huggingface.co/AISA-Framework" target="_blank" class="btn btn-secondary"> | |
| 🤗 HuggingFace | |
| <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M7 17L17 7M17 7H8M17 7v9"/></svg> | |
| </a> | |
| </div> | |
| <div class="aisa-content"> | |
| <div class="aisa-card"> | |
| <span class="card-num">01 · CONCEPT</span> | |
| <h3>What is AISA?</h3> | |
| <p>AISA is an <strong style="color:var(--paper);">implementation-neutral reference architecture</strong> for building agentic AI systems. It formalizes how reasoning, execution, infrastructure, evaluation, and governance interact to produce reliable, scalable, and auditable agent behavior.</p> | |
| </div> | |
| <div class="aisa-card"> | |
| <span class="card-num">02 · STRUCTURE</span> | |
| <h3>Architecture Overview</h3> | |
| <p>AISA defines six interacting layers — intelligence, cognition, tooling, evaluation, deployment, and governance — that together describe how a complete agentic system is designed, run, and audited.</p> | |
| </div> | |
| </div> | |
| <div class="aisa-citation"> | |
| <strong>Cite:</strong> Nacar, O., Deema, A., & Mohammed, A. (2026). <em>AISA: A Unified Architecture for Agentic AI Systems.</em> Zenodo. <a href="https://doi.org/10.5281/zenodo.18161880" target="_blank">https://doi.org/10.5281/zenodo.18161880</a> | |
| </div> | |
| </div> | |
| </section> | |
| <!-- ── TRACKS ────────────────────────────────────────────── --> | |
| <section id="tracks"> | |
| <div class="container"> | |
| <span class="section-tag">Three Tracks</span> | |
| <h2>Pick your challenge.</h2> | |
| <div class="ar-heading" lang="ar">اختر التحدي الذي يناسبك.</div> | |
| <p class="section-sub">Submit to Track A, Track B, or both. Every submission is automatically scored on Track C for dialect robustness.</p> | |
| <div class="tracks-grid"> | |
| <div class="track-card a"> | |
| <span class="track-id">TRACK A · CORE</span> | |
| <h3>Function Call Detection & Selection</h3> | |
| <p>The flagship track. Given an Arabic query and candidate tools, decide / select / extract.</p> | |
| <ul> | |
| <li>Binary call decision</li> | |
| <li>Function name selection</li> | |
| <li>Argument extraction (JSON)</li> | |
| <li>Open to all model architectures</li> | |
| </ul> | |
| </div> | |
| <div class="track-card b"> | |
| <span class="track-id">TRACK B · REASONING</span> | |
| <h3>Reasoning-Augmented Calling</h3> | |
| <p>Everything in Track A, plus an Arabic reasoning trace inside <code style="color:var(--lavender);"><think></code> blocks before the tool call.</p> | |
| <ul> | |
| <li>All Track A requirements</li> | |
| <li>Arabic reasoning generation</li> | |
| <li>Reasoning-action consistency scored</li> | |
| <li>For interpretable agentic AI</li> | |
| </ul> | |
| </div> | |
| <div class="track-card c"> | |
| <span class="track-id">TRACK C · DIAGNOSTIC</span> | |
| <h3>Cross-Dialect Robustness</h3> | |
| <p>Not a separate submission — an automatic dialect-stratified breakdown of your Track A or B results.</p> | |
| <ul> | |
| <li>MSA · Gulf · Egyptian</li> | |
| <li>Levantine · Maghrebi</li> | |
| <li>Per-dialect FnAcc + ArgEM</li> | |
| <li>Dialect gap score (max−min)</li> | |
| </ul> | |
| </div> | |
| </div> | |
| </div> | |
| </section> | |
| <!-- ── DATA ──────────────────────────────────────────────── --> | |
| <section id="data" class="data"> | |
| <div class="container"> | |
| <span class="section-tag">The Dataset</span> | |
| <h2>12,125 Arabic queries. Real domains. Real dialects.</h2> | |
| <div class="ar-heading" lang="ar">١٢٬١٢٥ استعلامًا عربيًا · مجالات حقيقية · لهجات حقيقية.</div> | |
| <p class="section-sub"> | |
| Hosted on Hugging Face at | |
| <a href="https://huggingface.co/datasets/TuwaiqAcademy/AISA-ArabicFC" target="_blank" style="color:var(--teal); font-family:'JetBrains Mono',monospace; font-size:15px;">TuwaiqAcademy/AISA-ArabicFC</a>. | |
| Training and development splits available now — blind test set released July 20, 2026. | |
| </p> | |
| <div class="data-grid"> | |
| <table class="data-table"> | |
| <thead> | |
| <tr><th>Split</th><th>Samples</th><th>Notes</th></tr> | |
| </thead> | |
| <tbody> | |
| <tr><td>Train</td><td>10,550</td><td>Available now</td></tr> | |
| <tr><td>Dev</td><td>525</td><td>Available now</td></tr> | |
| <tr><td>Test (blind)</td><td>1,050</td><td>Released July 20</td></tr> | |
| <tr><td>Positive samples</td><td>12,000</td><td>Tool call required</td></tr> | |
| <tr><td>Negative samples</td><td>125</td><td>No-call cases</td></tr> | |
| <tr><td>Reasoning traces</td><td>12,000</td><td>For Track B</td></tr> | |
| </tbody> | |
| </table> | |
| <div class="data-card"> | |
| <h3><span class="icon">↓</span> Load it in 3 lines</h3> | |
| <div class="code-block"><span class="c"># pip install datasets</span> | |
| <span class="k">from</span> datasets <span class="k">import</span> load_dataset | |
| ds = load_dataset(<span class="s">"TuwaiqAcademy/AISA-ArabicFC"</span>) | |
| print(ds[<span class="s">"train"</span>][<span class="s">0</span>])</div> | |
| <h3 style="margin-top:24px;"><span class="icon">i</span> Dialect breakdown</h3> | |
| <table class="data-table" style="margin-top:12px;"> | |
| <thead><tr><th>Dialect</th><th>%</th></tr></thead> | |
| <tbody> | |
| <tr><td>Modern Standard Arabic (MSA)</td><td>58.3%</td></tr> | |
| <tr><td>Levantine</td><td>16.9%</td></tr> | |
| <tr><td>Egyptian</td><td>12.2%</td></tr> | |
| <tr><td>Gulf</td><td>11.3%</td></tr> | |
| <tr><td>Maghrebi</td><td>1.3%</td></tr> | |
| </tbody> | |
| </table> | |
| </div> | |
| </div> | |
| <h3 style="margin-top:60px; font-size:20px; font-weight:700;">Eight service domains</h3> | |
| <p style="color:var(--muted); margin-top:6px; font-size:15px;">Real-world Arabic services. Tools designed by domain experts.</p> | |
| <div class="domains-grid"> | |
| <div class="domain-tag"><div class="d-name">🏥 Healthcare</div><div class="d-tools">book_doctor_appointment · search_medications · check_insurance_coverage</div></div> | |
| <div class="domain-tag"><div class="d-name">🏦 Banking & Finance</div><div class="d-tools">transfer_money · convert_currency · calculate_customs</div></div> | |
| <div class="domain-tag"><div class="d-name">🏛️ Government Services</div><div class="d-tools">check_visa_status · check_iqama_status · check_traffic_violations</div></div> | |
| <div class="domain-tag"><div class="d-name">🕌 Islamic Services</div><div class="d-tools">get_qibla_direction · calculate_zakat · search_quran · calculate_inheritance</div></div> | |
| <div class="domain-tag"><div class="d-name">✈️ Travel</div><div class="d-tools">search_hotels · search_umrah_packages</div></div> | |
| <div class="domain-tag"><div class="d-name">🌤️ Weather & Environment</div><div class="d-tools">get_weather · get_air_quality</div></div> | |
| <div class="domain-tag"><div class="d-name">🛒 E-commerce</div><div class="d-tools">compare_prices · order_food</div></div> | |
| <div class="domain-tag"><div class="d-name">🔧 Utilities</div><div class="d-tools">translate_text · calculate_end_of_service</div></div> | |
| </div> | |
| </div> | |
| </section> | |
| <!-- ── METRICS ───────────────────────────────────────────── --> | |
| <section id="metrics"> | |
| <div class="container"> | |
| <span class="section-tag">Evaluation</span> | |
| <h2>How submissions are scored.</h2> | |
| <div class="ar-heading" lang="ar">كيفية تقييم المشاركات.</div> | |
| <p class="section-sub">Two metrics, one weighted composite per track. Argument extraction is weighted higher because it's the primary challenge. Official evaluation script will be released open-source.</p> | |
| <div class="formula-stack"> | |
| <div class="formula-box"> | |
| <div class="formula-label">Track A</div> | |
| <div class="formula"> | |
| <span class="m">Overall</span> = | |
| <span class="w">0.40</span> · FnAcc + | |
| <span class="w">0.60</span> · <span style="color:var(--orange);">ArgEM</span> | |
| </div> | |
| </div> | |
| <div class="formula-box"> | |
| <div class="formula-label">Track B</div> | |
| <div class="formula"> | |
| <span class="m">Overall</span> = | |
| <span class="w">0.30</span> · FnAcc + | |
| <span class="w">0.50</span> · <span style="color:var(--orange);">ArgEM</span> + | |
| <span class="w">0.20</span> · ThinkRate | |
| </div> | |
| </div> | |
| </div> | |
| <div class="metrics-grid"> | |
| <div class="metric-card weight"> | |
| <span class="weight-pill">0.60 / 0.50</span> | |
| <div class="m-name" style="color:var(--orange);">ArgEM — Argument Exact Match ★</div> | |
| <div class="m-desc">Strict match of all predicted argument key-value pairs. The headline metric — small fine-tuned models top out around <strong style="color:var(--paper);">0.541</strong>, GPT-4o sits at <strong style="color:var(--paper);">0.070</strong>. Massive room to improve.</div> | |
| </div> | |
| <div class="metric-card weight"> | |
| <span class="weight-pill">0.40 / 0.30</span> | |
| <div class="m-name">FnAcc — Function Name Accuracy</div> | |
| <div class="m-desc">Exact match of the predicted function name (or <code style="color:var(--teal);">"none"</code> for negatives — this also penalises hallucinated calls).</div> | |
| </div> | |
| <div class="metric-card weight"> | |
| <span class="weight-pill">0.20</span> | |
| <div class="m-name" style="color:var(--lavender);">ThinkRate — Track B only</div> | |
| <div class="m-desc">Did the system produce an Arabic reasoning trace before the tool call? Best baseline: <strong style="color:var(--paper);">0.868</strong>.</div> | |
| </div> | |
| <div class="metric-card weight"> | |
| <span class="weight-pill">Diagnostic</span> | |
| <div class="m-name">Dialect gap (Track C)</div> | |
| <div class="m-desc">Per-dialect FnAcc + ArgEM, plus the max−min gap. Reported for analysis, not ranking. Gulf and Levantine are the hardest.</div> | |
| </div> | |
| </div> | |
| </div> | |
| </section> | |
| <!-- ── BASELINES ─────────────────────────────────────────── --> | |
| <section id="baselines" class="baselines"> | |
| <div class="container"> | |
| <span class="section-tag">Pilot Results</span> | |
| <h2>What the field looks like today.</h2> | |
| <div class="ar-heading" lang="ar">واقع الأداء في المجال اليوم.</div> | |
| <p class="section-sub">Four systems evaluated on the held-out test set. The takeaway: function selection is approachable. <strong style="color:var(--orange);">Argument exact match is wide open.</strong></p> | |
| <div class="baseline-table-wrap"> | |
| <table class="baseline-table"> | |
| <thead> | |
| <tr> | |
| <th>System</th> | |
| <th class="num-col">FnAcc</th> | |
| <th class="num-col highlight-col">ArgEM ★</th> | |
| <th class="num-col">Overall (A)</th> | |
| <th class="num-col">Overall (B)</th> | |
| </tr> | |
| </thead> | |
| <tbody> | |
| <tr class="best"> | |
| <td> | |
| <div class="sys-name">AISA-Think</div> | |
| <div class="sys-desc">Gemma 3 (270M) + LoRA · reasoning-augmented</div> | |
| </td> | |
| <td class="num-col"><strong>0.982</strong></td> | |
| <td class="num-col highlight-col"><strong>0.541</strong></td> | |
| <td class="num-col"><strong>0.717</strong></td> | |
| <td class="num-col"><strong>0.739</strong></td> | |
| </tr> | |
| <tr> | |
| <td> | |
| <div class="sys-name">GPT-4o</div> | |
| <div class="sys-desc">Zero-shot prompting</div> | |
| </td> | |
| <td class="num-col">0.927</td> | |
| <td class="num-col highlight-col">0.070</td> | |
| <td class="num-col">0.413</td> | |
| <td class="num-col">0.313</td> | |
| </tr> | |
| <tr> | |
| <td> | |
| <div class="sys-name">GPT-4o</div> | |
| <div class="sys-desc">3-shot prompting</div> | |
| </td> | |
| <td class="num-col">0.854</td> | |
| <td class="num-col highlight-col">0.122</td> | |
| <td class="num-col">0.415</td> | |
| <td class="num-col">0.317</td> | |
| </tr> | |
| <tr class="dim"> | |
| <td> | |
| <div class="sys-name">Random</div> | |
| <div class="sys-desc">Random tool from candidate set</div> | |
| </td> | |
| <td class="num-col">0.047</td> | |
| <td class="num-col highlight-col">0.033</td> | |
| <td class="num-col">0.039</td> | |
| <td class="num-col">0.031</td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <div class="baseline-footnote">Track B Think-Before-Call rate: AISA-Think <strong>0.868</strong>, others <strong>0.000</strong>.</div> | |
| </div> | |
| <div class="findings-grid"> | |
| <div class="finding"> | |
| <div class="finding-icon" style="background:rgba(244,166,100,0.15); color:var(--orange);">🎯</div> | |
| <h3>Argument extraction is the core challenge</h3> | |
| <p>Best ArgEM is <strong>0.541</strong>; GPT-4o achieves <strong>0.070</strong>. Hard cases include date format normalization, numeric type handling, and dialectal argument phrasing.</p> | |
| </div> | |
| <div class="finding"> | |
| <div class="finding-icon" style="background:rgba(87,227,216,0.15); color:var(--teal);">⚡</div> | |
| <h3>Small fine-tuned models beat GPT-4o</h3> | |
| <p>A 270M LoRA model outperforms GPT-4o across every metric — showing the value of task-specific Arabic training over scale alone.</p> | |
| </div> | |
| <div class="finding"> | |
| <div class="finding-icon" style="background:rgba(163,128,255,0.15); color:var(--lavender);">🌍</div> | |
| <h3>Dialect gaps are significant</h3> | |
| <p>FnAcc varies by up to <strong>17.8pp</strong> across dialects. Gulf and Levantine Arabic are consistently the hardest — Track C surfaces this directly.</p> | |
| </div> | |
| </div> | |
| </div> | |
| </section> | |
| <!-- ── PRIZES ────────────────────────────────────────────── --> | |
| <section id="prizes" class="prizes"> | |
| <div class="container"> | |
| <span class="section-tag">Prizes</span> | |
| <h2>$1,000 for the top three systems.</h2> | |
| <div class="ar-heading" lang="ar">جوائز نقدية للأنظمة الثلاثة الأولى.</div> | |
| <p class="section-sub">Cash prizes awarded to the best-performing systems on the final test set leaderboard. Open to every registered team worldwide — no fees, no nationality requirements.</p> | |
| <div class="prize-grid"> | |
| <div class="prize-card second"> | |
| <div class="prize-medal">🥈</div> | |
| <div class="prize-rank">2nd Place</div> | |
| <div class="prize-amount">$300</div> | |
| <div class="prize-label">Cash Prize</div> | |
| </div> | |
| <div class="prize-card first"> | |
| <div class="prize-medal">🥇</div> | |
| <div class="prize-rank">1st Place · Winner</div> | |
| <div class="prize-amount">$500</div> | |
| <div class="prize-label">Cash Prize</div> | |
| </div> | |
| <div class="prize-card third"> | |
| <div class="prize-medal">🥉</div> | |
| <div class="prize-rank">3rd Place</div> | |
| <div class="prize-amount">$200</div> | |
| <div class="prize-label">Cash Prize</div> | |
| </div> | |
| </div> | |
| <div class="prize-total"> | |
| <div class="pt-amount">$1,000 total</div> | |
| <div class="pt-text"> | |
| Ranking is based on the <strong>Track A Overall score</strong> on the blind test set (released July 20). Winners announced July 30 and recognised at <strong>ArabicNLP 2026 in Budapest</strong>. | |
| </div> | |
| </div> | |
| </div> | |
| </section> | |
| <!-- ── PARTICIPATE ───────────────────────────────────────── --> | |
| <section id="participate" class="participate"> | |
| <div class="container"> | |
| <span class="section-tag">How to Participate</span> | |
| <h2>From registration to leaderboard to paper.</h2> | |
| <div class="ar-heading" lang="ar">من التسجيل إلى لوحة الصدارة إلى الورقة العلمية.</div> | |
| <p class="section-sub">The shared task runs in four clear phases. Registration opens first, then the data drops, then teams iterate on the live dev leaderboard, then the blind test settles the final ranking.</p> | |
| <div class="steps"> | |
| <a href="https://tuwaiq.edu.sa/form/rL7Bl3wq" target="_blank" class="step" style="text-decoration:none; color:inherit; display:block;"> | |
| <div class="step-num">01</div> | |
| <h3>Register your team</h3> | |
| <p> | |
| <strong style="color:var(--teal);">Registration is open now</strong> · sign up your team — name, leader, registered email, HF account. Locks you in to submit on the leaderboard from day one. Closes <strong style="color:var(--paper);">July 20</strong>.<br/> | |
| <span style="color:var(--teal); font-weight:600;">Open the form →</span> | |
| </p> | |
| </a> | |
| <div class="step"> | |
| <div class="step-num">02</div> | |
| <h3>Get data, baselines & eval</h3> | |
| <p> | |
| <strong style="color:var(--lavender);">Released June 1</strong> · we drop the training + dev splits on Hugging Face, the official evaluation script, and the baseline model code. Pick any approach — fine-tuned LLMs, prompting, retrieval, hybrid — and get building. | |
| </p> | |
| </div> | |
| <div class="step"> | |
| <div class="step-num">03</div> | |
| <h3>Climb the dev leaderboard</h3> | |
| <p> | |
| <strong style="color:var(--orange);">June 1 → July 20</strong> · iterate freely. Upload predictions to the | |
| <a href="https://huggingface.co/spaces/TuwaiqAcademy/AISA-ArabicFC-SharedTask-Leaderboard" target="_blank">live leaderboard</a>, | |
| get auto-scored on the dev split, watch your rank update. Submit as many system variants as you want — the dev board is your sandbox. | |
| </p> | |
| </div> | |
| <div class="step"> | |
| <div class="step-num">04</div> | |
| <h3>Test set & paper</h3> | |
| <p> | |
| <strong style="color:var(--green);">July 20 → Aug 22</strong> · the blind <strong style="color:var(--paper);">test set</strong> drops July 20. Run your best system, submit final predictions. Results published <strong style="color:var(--paper);">July 30</strong>. Camera-ready system description paper due <strong style="color:var(--paper);">August 22</strong>. | |
| </p> | |
| </div> | |
| </div> | |
| <a href="https://tuwaiq.edu.sa/form/rL7Bl3wq" target="_blank" class="form-notice" style="text-decoration:none; color:inherit;"> | |
| <div class="fn-icon">📝</div> | |
| <div class="fn-text"> | |
| <div class="fn-title">Registration is open — sign up your team now</div> | |
| <div class="fn-desc">Open the official Tuwaiq Academy registration form: <strong style="color:var(--paper);">tuwaiq.edu.sa/form/rL7Bl3wq</strong>. Closes <strong style="color:var(--paper);">July 20</strong>.</div> | |
| </div> | |
| <span class="fn-pill"><span class="dot"></span> Open form →</span> | |
| </a> | |
| <div class="cite-notice"> | |
| <div class="cn-head"> | |
| <svg viewBox="0 0 24 24" width="20" height="20" fill="none" stroke="currentColor" stroke-width="2"><path d="M14 2H6a2 2 0 00-2 2v16a2 2 0 002 2h12a2 2 0 002-2V8z"/><path d="M14 2v6h6M16 13H8M16 17H8M10 9H8"/></svg> | |
| <span>Required citations for system description papers</span> | |
| </div> | |
| <p>All participating system description papers must cite the three references below. See the <a href="#citation">Citation</a> section for ready-to-use BibTeX entries.</p> | |
| <ul> | |
| <li><strong>Shared task:</strong> Najar et al. (2026) — <em>AISA-ArabicFC: Arabic Function Calling for Agentic AI Systems</em></li> | |
| <li><strong>Architecture:</strong> Nacar, Deema, & Mohammed (2026) — <em>AISA: A Unified Architecture for Agentic AI Systems</em></li> | |
| <li><strong>Methodology:</strong> Nacar et al. (2026) — <em>From Language to Action in Arabic: Reliable Structured Tool Calling via Data-Centric Fine-Tuning</em></li> | |
| </ul> | |
| </div> | |
| </div> | |
| </section> | |
| <!-- ── DATES ─────────────────────────────────────────────── --> | |
| <section id="dates"> | |
| <div class="container"> | |
| <span class="section-tag">Timeline</span> | |
| <h2>Important dates.</h2> | |
| <div class="ar-heading" lang="ar">تواريخ مهمّة.</div> | |
| <p class="section-sub">All deadlines are AoE.</p> | |
| <div class="timeline"> | |
| <div class="tl-item"> | |
| <div class="tl-date">May 16, 2026</div> | |
| <div class="tl-title">Task launch</div> | |
| <div class="tl-desc">Shared task website live · registration opens · leaderboard online</div> | |
| </div> | |
| <div class="tl-item"> | |
| <div class="tl-date">June 1, 2026</div> | |
| <div class="tl-title">Training / development data · baseline code · evaluation scripts released</div> | |
| <div class="tl-desc">Hugging Face dataset goes public · baseline model code published · official scorer released open-source</div> | |
| </div> | |
| <div class="tl-item"> | |
| <div class="tl-date">July 20, 2026</div> | |
| <div class="tl-title">Registration deadline · Blind test data released</div> | |
| <div class="tl-desc">Last day to register your team on Hugging Face. Test set distributed to registered teams.</div> | |
| </div> | |
| <div class="tl-item"> | |
| <div class="tl-date">July 30, 2026</div> | |
| <div class="tl-title">Final results released</div> | |
| <div class="tl-desc">Leaderboard published. Per-track and per-dialect breakdowns.</div> | |
| </div> | |
| <div class="tl-item"> | |
| <div class="tl-date">August 22, 2026</div> | |
| <div class="tl-title">Camera-ready system description papers due</div> | |
| <div class="tl-desc">Participants submit final system papers describing their approach.</div> | |
| </div> | |
| <div class="tl-item"> | |
| <div class="tl-date">September 1, 2026</div> | |
| <div class="tl-title">Shared task overview paper due</div> | |
| <div class="tl-desc">Organizers' overview paper covering task, methodology, and results.</div> | |
| </div> | |
| <div class="tl-item"> | |
| <div class="tl-date">September 10, 2026</div> | |
| <div class="tl-title">Conference camera-ready deadline</div> | |
| <div class="tl-desc">Final paper revisions due for the proceedings.</div> | |
| </div> | |
| <div class="tl-item"> | |
| <div class="tl-date">October 24–29, 2026</div> | |
| <div class="tl-title">ArabicNLP 2026 / EMNLP 2026 — Budapest, Hungary</div> | |
| <div class="tl-desc">Presentation at the Fourth Arabic Natural Language Processing Conference, co-located with EMNLP 2026.</div> | |
| </div> | |
| </div> | |
| </div> | |
| </section> | |
| <!-- ── RESOURCES ─────────────────────────────────────────── --> | |
| <section id="resources" class="resources"> | |
| <div class="container"> | |
| <span class="section-tag">Resources</span> | |
| <h2>Everything you need to compete.</h2> | |
| <div class="ar-heading" lang="ar">كل ما تحتاجه للمشاركة في المنافسة.</div> | |
| <p class="section-sub">Grouped the way you'll use them: build, read, get help.</p> | |
| <!-- GROUP 1 — BUILD --> | |
| <div class="res-group"> | |
| <div class="res-group-head"> | |
| <span class="rg-num">01</span> | |
| <div> | |
| <div class="rg-title">Build your system</div> | |
| <div class="rg-desc">Data, baseline, evaluation script — everything you need to produce a valid submission.</div> | |
| </div> | |
| </div> | |
| <div class="build-grid"> | |
| <a href="https://huggingface.co/datasets/TuwaiqAcademy/AISA-ArabicFC" target="_blank" class="build-card"> | |
| <span class="bc-step">Step 1</span> | |
| <div class="bc-icon-wrap teal-bg">📊</div> | |
| <h3>Get the data</h3> | |
| <p>Train + dev splits are live. Blind test arrives <strong>July 20</strong>.</p> | |
| <span class="bc-cta teal-fg">Open dataset →</span> | |
| </a> | |
| <a href="https://huggingface.co/TuwaiqAcademy/AISA-AR-FunctionCall-Think" target="_blank" class="build-card"> | |
| <span class="bc-step">Step 2</span> | |
| <div class="bc-icon-wrap lavender-bg">🧠</div> | |
| <h3>Beat the baseline</h3> | |
| <p><strong>AISA-Think</strong> — Gemma 3 (270M) + LoRA. <strong>0.541</strong> ArgEM is the bar.</p> | |
| <span class="bc-cta lavender-fg">Open model →</span> | |
| </a> | |
| <a href="https://huggingface.co/spaces/TuwaiqAcademy/AISA-ArabicFC-SharedTask-Leaderboard" target="_blank" class="build-card"> | |
| <span class="bc-step">Step 3</span> | |
| <div class="bc-icon-wrap orange-bg">⚖️</div> | |
| <h3>Evaluate & submit</h3> | |
| <p>Upload dev predictions, get scored instantly, land on the <strong>live leaderboard</strong>.</p> | |
| <span class="bc-cta orange-fg">Open leaderboard →</span> | |
| </a> | |
| </div> | |
| </div> | |
| <!-- GROUP 2 — READ --> | |
| <div class="res-group"> | |
| <div class="res-group-head"> | |
| <span class="rg-num">02</span> | |
| <div> | |
| <div class="rg-title">Read the research</div> | |
| <div class="rg-desc">Background on the architecture and the methodology behind the baseline.</div> | |
| </div> | |
| </div> | |
| <div class="res-grid"> | |
| <a href="https://doi.org/10.5281/zenodo.18161880" target="_blank" class="res-card"> | |
| <div class="res-icon" style="background:rgba(163,128,255,0.15); color:var(--lavender);">📄</div> | |
| <div class="res-title">AISA architecture paper <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M7 17L17 7M17 7H8M17 7v9"/></svg></div> | |
| <div class="res-desc">A Unified Architecture for Agentic AI Systems — design, evaluation, governance, deployment layers.</div> | |
| <span class="res-link">Zenodo · 10.5281/zenodo.18161880</span> | |
| </a> | |
| <a href="https://arxiv.org/abs/2603.16901" target="_blank" class="res-card"> | |
| <div class="res-icon" style="background:rgba(244,166,100,0.15); color:var(--orange);">📜</div> | |
| <div class="res-title">Methodology paper <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M7 17L17 7M17 7H8M17 7v9"/></svg></div> | |
| <div class="res-desc">From Language to Action in Arabic — the data-centric fine-tuning recipe behind the baseline.</div> | |
| <span class="res-link">arXiv:2603.16901</span> | |
| </a> | |
| </div> | |
| </div> | |
| <!-- GROUP 3 — CONFERENCE & HELP --> | |
| <div class="res-group"> | |
| <div class="res-group-head"> | |
| <span class="rg-num">03</span> | |
| <div> | |
| <div class="rg-title">Conference & community</div> | |
| <div class="rg-desc">Where you'll present your work and how to reach the organizers.</div> | |
| </div> | |
| </div> | |
| <div class="res-grid"> | |
| <a href="https://arabicnlp2026.sigarab.org/" target="_blank" class="res-card"> | |
| <div class="res-icon" style="background:rgba(255,129,129,0.15); color:var(--red);">🏛️</div> | |
| <div class="res-title">ArabicNLP 2026 <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M7 17L17 7M17 7H8M17 7v9"/></svg></div> | |
| <div class="res-desc">The Fourth Arabic NLP Conference. Co-located with EMNLP 2026 in Budapest, Hungary.</div> | |
| <span class="res-link">arabicnlp2026.sigarab.org</span> | |
| </a> | |
| <a href="mailto:trdc@tuwaiq.edu.sa" class="res-card"> | |
| <div class="res-icon" style="background:rgba(77,150,255,0.15); color:var(--blue);">📧</div> | |
| <div class="res-title">Get help <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M7 17L17 7M17 7H8M17 7v9"/></svg></div> | |
| <div class="res-desc">Questions about the data, evaluation, or submission? Reach the organizers directly.</div> | |
| <span class="res-link">trdc@tuwaiq.edu.sa</span> | |
| </a> | |
| </div> | |
| </div> | |
| </div> | |
| </section> | |
| <!-- ── ORGANIZERS ────────────────────────────────────────── --> | |
| <section id="organizers"> | |
| <div class="container"> | |
| <span class="section-tag">Organizers</span> | |
| <h2>Organized by Tuwaiq Academy.</h2> | |
| <div class="ar-heading" lang="ar">بتنظيم من أكاديمية طويق.</div> | |
| <p class="section-sub">A multi-disciplinary team building Arabic-native AI capabilities.</p> | |
| <div class="org-grid"> | |
| <div class="org-card"> | |
| <div class="org-avatar">ON</div> | |
| <div class="org-name">Omer Nacar</div> | |
| <div class="org-aff">Tuwaiq Academy</div> | |
| </div> | |
| <div class="org-card"> | |
| <div class="org-avatar">MK</div> | |
| <div class="org-name">Mohammed Al Khalifa</div> | |
| <div class="org-aff">Tuwaiq Academy</div> | |
| </div> | |
| <div class="org-card"> | |
| <div class="org-avatar">SA</div> | |
| <div class="org-name">Saeed Alzaharani</div> | |
| <div class="org-aff">Tuwaiq Academy</div> | |
| </div> | |
| </div> | |
| <div class="contact-line"> | |
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| <span>Contact: <a href="mailto:trdc@tuwaiq.edu.sa">trdc@tuwaiq.edu.sa</a></span> | |
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| <!-- ── CITATION ──────────────────────────────────────────── --> | |
| <section id="citation" class="citation"> | |
| <div class="container"> | |
| <span class="section-tag">Required Citations</span> | |
| <h2>Cite these three works.</h2> | |
| <div class="ar-heading" lang="ar">يُرجى الاستشهاد بهذه الأعمال الثلاثة.</div> | |
| <p class="section-sub">All system description papers must cite the shared task, the AISA architecture, and the methodology paper. Click any block to copy.</p> | |
| <div class="bib-list"> | |
| <!-- 1. Shared task --> | |
| <div class="bib-entry"> | |
| <div class="bib-head"> | |
| <div> | |
| <div class="bib-tag">01 · Shared Task</div> | |
| <div class="bib-title">AISA-ArabicFC: Arabic Function Calling for Agentic AI Systems</div> | |
| <div class="bib-meta">Najar, Al Khalifa & Alzaharani · ArabicNLP 2026 · Budapest</div> | |
| </div> | |
| <button class="copy-btn" data-target="bib-1"> | |
| <svg viewBox="0 0 24 24" width="14" height="14" fill="none" stroke="currentColor" stroke-width="2"><rect x="9" y="9" width="13" height="13" rx="2"/><path d="M5 15H4a2 2 0 01-2-2V4a2 2 0 012-2h9a2 2 0 012 2v1"/></svg> | |
| <span>Copy</span> | |
| </button> | |
| </div> | |
| <pre class="bibtex" id="bib-1"><span class="k">@inproceedings</span>{<span class="f">najar2026aisaarabicfc</span>, | |
| <span class="f">title</span> = <span class="v">{{AISA-ArabicFC}: Arabic Function Calling for Agentic AI Systems}</span>, | |
| <span class="f">author</span> = <span class="v">{Najar, Omar and Al Khalifa, Mohammed and Alzaharani, Saeed}</span>, | |
| <span class="f">booktitle</span> = <span class="v">{Proceedings of the Fourth Arabic Natural Language Processing Conference (ArabicNLP 2026)}</span>, | |
| <span class="f">year</span> = <span class="v">{2026}</span>, | |
| <span class="f">address</span> = <span class="v">{Budapest, Hungary}</span>, | |
| <span class="f">publisher</span> = <span class="v">{Association for Computational Linguistics}</span> | |
| }</pre> | |
| </div> | |
| <!-- 2. AISA architecture --> | |
| <div class="bib-entry"> | |
| <div class="bib-head"> | |
| <div> | |
| <div class="bib-tag">02 · Architecture</div> | |
| <div class="bib-title">AISA: A Unified Architecture for Agentic AI Systems</div> | |
| <div class="bib-meta">Nacar, Deema & Mohammed · Zenodo 2026 · <a href="https://doi.org/10.5281/zenodo.18161880" target="_blank" style="color:var(--teal);">10.5281/zenodo.18161880</a></div> | |
| </div> | |
| <button class="copy-btn" data-target="bib-2"> | |
| <svg viewBox="0 0 24 24" width="14" height="14" fill="none" stroke="currentColor" stroke-width="2"><rect x="9" y="9" width="13" height="13" rx="2"/><path d="M5 15H4a2 2 0 01-2-2V4a2 2 0 012-2h9a2 2 0 012 2v1"/></svg> | |
| <span>Copy</span> | |
| </button> | |
| </div> | |
| <pre class="bibtex" id="bib-2"><span class="k">@misc</span>{<span class="f">nacar2026aisa</span>, | |
| <span class="f">title</span> = <span class="v">{{AISA}: A Unified Architecture for Agentic AI Systems}</span>, | |
| <span class="f">author</span> = <span class="v">{Nacar, Omer and Deema, A. and Mohammed, A.}</span>, | |
| <span class="f">year</span> = <span class="v">{2026}</span>, | |
| <span class="f">publisher</span> = <span class="v">{Zenodo}</span>, | |
| <span class="f">doi</span> = <span class="v">{10.5281/zenodo.18161880}</span>, | |
| <span class="f">url</span> = <span class="v">{https://doi.org/10.5281/zenodo.18161880}</span> | |
| }</pre> | |
| </div> | |
| <!-- 3. Methodology paper --> | |
| <div class="bib-entry"> | |
| <div class="bib-head"> | |
| <div> | |
| <div class="bib-tag">03 · Methodology</div> | |
| <div class="bib-title">From Language to Action in Arabic: Reliable Structured Tool Calling via Data-Centric Fine-Tuning</div> | |
| <div class="bib-meta">Nacar, Alquffari, Alsharideh, AlOtaibi et al. · arXiv:2603.16901 · 2026</div> | |
| </div> | |
| <button class="copy-btn" data-target="bib-3"> | |
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| <span>Copy</span> | |
| </button> | |
| </div> | |
| <pre class="bibtex" id="bib-3"><span class="k">@article</span>{<span class="f">nacar2026language</span>, | |
| <span class="f">title</span> = <span class="v">{From Language to Action in Arabic: Reliable Structured Tool Calling via Data-Centric Fine-Tuning}</span>, | |
| <span class="f">author</span> = <span class="v">{Nacar, Omer and Alquffari, Deema and Alsharideh, Saleh and AlOtaibi, Adeem and Alabdulkarim, Abdulaziz and Alhazmi, Leen and Alomar, Nada and Alzubaidi, Wareef and Alsultan, Nada and Alrabghi, Ahmed and others}</span>, | |
| <span class="f">journal</span> = <span class="v">{arXiv preprint arXiv:2603.16901}</span>, | |
| <span class="f">year</span> = <span class="v">{2026}</span> | |
| }</pre> | |
| </div> | |
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