id
stringlengths 1
4
| tokens
sequence | ner_tags
sequence |
---|---|---|
200 | [
"Using",
"such",
"a",
"framework,",
"UnifiedQA",
"(Khashabi",
"et",
"al.,",
"2020)",
"integrates",
"20",
"QA",
"datasets",
"into",
"a",
"unified",
"format",
"for",
"training,",
"and",
"achieves",
"state-of-the-art",
"results",
"on",
"multiple",
"MCQA",
"datasets."
] | [
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
11,
0
] |
201 | [
"One",
"benefit",
"is",
"that",
"extensive",
"training",
"data",
"can",
"be",
"shared",
"across",
"different",
"tasks."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
202 | [
"As",
"illustrated",
"in",
"Figure",
"2a,",
"adopting",
"this",
"paradigm",
"for",
"MCQA,",
"the",
"question",
"Q",
"and",
"all",
"the",
"options",
"O1,",
"O2,",
"O3,",
"O4}",
"are",
"spliced",
"into",
"a",
"text",
"as",
"input,",
"and",
"the",
"correct",
"answer",
"O1",
"is",
"used",
"as",
"the",
"generation",
"target."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
11,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
203 | [
"Recently,",
"the",
"text-to-text",
"paradigm",
"has",
"achieved",
"breakthrough",
"results",
"on",
"many",
"NLP",
"tasks",
"(Raffel",
"et",
"al.,",
"2020;",
"Lewis",
"et",
"al.,",
"2020)."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
204 | [
"2.1",
"Text-to-Text",
"Paradigm",
"for",
"MCQA"
] | [
0,
0,
0,
0,
11
] |
205 | [
"2",
"Related",
"Work"
] | [
0,
0,
0
] |
206 | [
"Code",
"Our",
"code",
"is",
"available",
"on",
"GitHub1",
"under",
"the",
"Apache",
"Licence",
"2.0."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
207 | [
"Outline",
"We",
"discuss",
"related",
"work",
"in",
"Section",
"2,",
"introduce",
"GenMC",
"in",
"Section",
"3,",
"describe",
"the",
"experimental",
"setup",
"in",
"Section",
"4,",
"report",
"the",
"results",
"in",
"Section",
"5,",
"and",
"conclude",
"in",
"Section",
"6."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
208 | [
"It",
"significantly",
"outperforms",
"comparable",
"models,",
"in",
"particular,",
"text-to-text",
"models,",
"on",
"five",
"MCQA",
"datasets."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
11,
0
] |
209 | [
"We",
"refer",
"to",
"this",
"generation-enhanced",
"MCQA",
"model",
"as",
"GenMC."
] | [
0,
0,
0,
0,
0,
11,
0,
0,
1
] |
210 | [
"The",
"clue",
"representation",
"is",
"then",
"leveraged",
"by",
"an",
"encoder-based",
"model",
"to",
"read",
"the",
"options",
"and",
"make",
"prediction."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
211 | [
"With",
"this",
"idea,",
"we",
"propose",
"to",
"employ",
"a",
"pretrained",
"encoder-decoder",
"model",
"to",
"generate",
"a",
"clue",
"from",
"the",
"question",
"by",
"exploiting",
"its",
"underlying",
"knowledge,",
"without",
"seeing",
"and",
"being",
"strictly",
"confined",
"to",
"the",
"options",
"as",
"in",
"the",
"text-to-text",
"framework."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
212 | [
"Our",
"Contribution"
] | [
0,
0
] |
213 | [
"One",
"research",
"question",
"is",
"how",
"to",
"apply",
"pre-trained",
"encoder-decoder",
"models",
"in",
"a",
"more",
"natural",
"way",
"to",
"MCQA,",
"in",
"particular,",
"to",
"exploit",
"their",
"NLG",
"capabilities."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
11,
0,
0,
0,
0,
0,
0,
0
] |
214 | [
"Indeed,",
"Liu",
"et",
"al.",
"(2021)",
"have",
"found",
"that",
"in",
"classification",
"and",
"regression",
"tasks,",
"the",
"decoder",
"layer",
"is",
"often",
"under-utilized."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
215 | [
"However,",
"this",
"is",
"inconsistent",
"with",
"how",
"encoder-decoder",
"models",
"are",
"pre-trained",
"so",
"that",
"their",
"underlying",
"knowledge",
"may",
"not",
"be",
"sufficiently",
"exploited."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
216 | [
"Research",
"Question",
"To",
"fit",
"MCQA,",
"existing",
"implementations",
"of",
"the",
"text-to-text",
"framework",
"take",
"all",
"the",
"options",
"as",
"input",
"and",
"are",
"trained",
"to",
"generate",
"one",
"of",
"the",
"options,",
"i.e.,",
"to",
"copy",
"some",
"tokens",
"from",
"the",
"input."
] | [
0,
0,
0,
0,
11,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
217 | [
"This",
"is",
"enabled",
"by",
"the",
"text-to-text",
"framework,",
"which",
"transforms",
"data",
"in",
"different",
"tasks",
"into",
"a",
"unified",
"text-to-text",
"format",
"so",
"that",
"knowledge",
"spanning",
"many",
"and",
"various",
"tasks",
"can",
"be",
"learned,",
"aggregated,",
"and",
"used",
"by",
"a",
"single",
"model."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
218 | [
"However,",
"encoder-decoder",
"models",
"can",
"also",
"be",
"applied",
"to",
"MCQA",
"(Khashabi",
"et",
"al.,",
"2020;",
"Zhou",
"et",
"al.,",
"2021)."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
11,
0,
0,
0,
0,
0,
0,
0,
0
] |
219 | [
"T5",
"(Raffel",
"et",
"al.,",
"2020)",
"and",
"BART",
"(Lewis",
"et",
"al.,",
"2020)",
"are",
"encoder-decoder",
"models,",
"being",
"more",
"suitable",
"for",
"natural",
"language",
"generation",
"(NLG)",
"tasks."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
220 | [
"and",
"its",
"variants",
"such",
"as",
"RoBERTa",
"(Liu",
"et",
"al.,",
"2019)",
"and",
"ALBERT",
"(Lan",
"et",
"al.,",
"2020)",
"are",
"encoder-only",
"models,",
"being",
"more",
"suitable",
"for",
"natural",
"language",
"understanding",
"(NLU)",
"tasks",
"including",
"MCQA",
"and",
"other",
"classification",
"and",
"regression",
"tasks."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
11,
12,
12,
11,
0,
0,
11,
0,
0,
0,
0,
0,
0
] |
221 | [
"BERT",
"(Devlin",
"et",
"al.,",
"2019)"
] | [
0,
0,
0,
0,
0
] |
222 | [
"Basically",
"there",
"are",
"two",
"types",
"of",
"PLMs",
"that",
"are",
"suitable",
"for",
"different",
"tasks."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
223 | [
"MCQA",
"has",
"made",
"great",
"progress",
"with",
"the",
"development",
"of",
"pre-trained",
"language",
"models",
"(PLMs)."
] | [
11,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
224 | [
"Mihaylov",
"et",
"al.,",
"2018)",
"and",
"scientific",
"knowledge",
"(Clark",
"et",
"al.,",
"2018;",
"Khot",
"et",
"al.,",
"2020;",
"Huang",
"et",
"al.,",
"2019;",
"Li",
"et",
"al.,",
"2021),",
"and",
"have",
"reasoning",
"skills",
"such",
"as",
"multi-hop",
"reasoning",
"(Khot",
"et",
"al.,",
"2019)",
"and",
"logical",
"reasoning",
"(Yu",
"et",
"al.,",
"2020;",
"Liu",
"et",
"al.,",
"2020b;",
"Li",
"et",
"al.,",
"2022)."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
225 | [
"This",
"long-standing",
"challenge",
"in",
"natural",
"language",
"processing",
"(NLP)",
"requires",
"machines",
"to",
"have",
"a",
"wealth",
"of",
"knowledge,",
"such",
"as",
"commonsense",
"knowledge",
"(Talmor",
"et",
"al.,",
"2019;"
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
226 | [
"Multiple-choice",
"question",
"answering",
"(MCQA)",
"aims",
"at",
"selecting",
"the",
"correct",
"answer",
"from",
"a",
"set",
"of",
"options",
"given",
"a",
"question."
] | [
0,
0,
0,
11,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
227 | [
"Introduction"
] | [
0
] |
228 | [
"It",
"outperforms",
"textto-text",
"models",
"on",
"multiple",
"MCQA",
"datasets."
] | [
0,
0,
0,
0,
0,
0,
11,
0
] |
229 | [
"It",
"generates",
"a",
"clue",
"from",
"the",
"question",
"and",
"then",
"leverages",
"the",
"clue",
"to",
"enhance",
"a",
"reader",
"for",
"MCQA."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
11
] |
230 | [
"To",
"exploit",
"the",
"generation",
"capability",
"and",
"underlying",
"knowledge",
"of",
"a",
"pre-trained",
"encoder-decoder",
"model,",
"in",
"this",
"paper,",
"we",
"propose",
"a",
"generation-enhanced",
"MCQA",
"model",
"named",
"GenMC."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
11,
0,
0,
1
] |
231 | [
"However,",
"a",
"side",
"effect",
"of",
"twisting",
"a",
"generation",
"target",
"to",
"fit",
"the",
"classification",
"nature",
"of",
"MCQA",
"is",
"the",
"underutilization",
"of",
"the",
"decoder",
"and",
"the",
"knowledge",
"that",
"can",
"be",
"decoded."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
11,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
232 | [
"By",
"unifying",
"data",
"in",
"different",
"tasks",
"into",
"a",
"single",
"text-to-text",
"format,",
"it",
"trains",
"a",
"generative",
"encoder-decoder",
"model",
"which",
"is",
"both",
"powerful",
"and",
"universal."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
233 | [
"A",
"trending",
"paradigm",
"for",
"multiple-choice",
"question",
"answering",
"(MCQA)",
"is",
"using",
"a",
"text-to-text",
"framework."
] | [
0,
0,
0,
0,
11,
12,
12,
11,
0,
0,
0,
0,
0
] |
234 | [
"Abstract"
] | [
0
] |
235 | [
"Clues",
"Before",
"Answers:",
"Generation-Enhanced",
"Multiple-Choice",
"QA"
] | [
0,
0,
0,
0,
0,
0
] |
236 | [
"Figure",
"6",
"and",
"Figure",
"7",
"display",
"the",
"10",
"first",
"dialog",
"samples",
"produced",
"at",
"test",
"time",
"on",
"CLEVR,",
"while",
"figures",
"8,",
"9,",
"and",
"10",
"display",
"the",
"15",
"first",
"dialog",
"samples",
"produced",
"at",
"test",
"time",
"on",
"VQAv2."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
13,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
13
] |
237 | [
"D",
"Additional",
"VQG",
"Samples"
] | [
0,
0,
11,
0
] |
238 | [
"(b)",
"Language",
"Grounding",
"pairwise",
"comparison"
] | [
0,
0,
0,
0,
0
] |
239 | [
"(a)",
"Language",
"Quality",
"pairwise",
"comparison"
] | [
0,
0,
0,
0,
0
] |
240 | [
"Figure",
"5",
"displays",
"one",
"pairwise",
"comparison",
"example",
"for",
"the",
"three",
"sections,",
"and",
"a",
"full",
"form",
"example",
"is",
"available",
"at",
"the",
"following",
"url:",
"https://forms.gle/kkL38x31wF7A9YKx5."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
241 | [
"The",
"evaluation",
"of",
"syntax",
"errors",
"was",
"made",
"within",
"the",
"diversity",
"section:",
"for",
"each",
"questions",
"pair,",
"we",
"asked",
"participants",
"to",
"tick",
"the",
"questions",
"if",
"they",
"are",
"grammatically",
"incorrect."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
242 | [
"Each",
"pairwise",
"comparison",
"is",
"sampled",
"uniformly",
"over",
"the",
"50",
"first",
"question",
"samples",
"generated",
"by",
"the",
"algorithms",
"at",
"test",
"time."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
243 | [
"Given",
"the",
"five",
"evaluated",
"models,",
"there",
"are",
"ten",
"different",
"model",
"pairs:",
"each",
"section",
"of",
"the",
"form",
"contains",
"10",
"pairwise",
"comparison",
"covering",
"all",
"the",
"possible",
"model",
"pairs",
"for",
"the",
"criteria."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
244 | [
"For",
"the",
"Human",
"Evaluation",
"study,",
"we",
"designed",
"one",
"form",
"per",
"participant,",
"with",
"three",
"sections",
"evaluating",
"respectively",
"the",
"language",
"quality,",
"language",
"grounding",
"and",
"diversity",
"criteria."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
245 | [
"C",
"Human",
"Evaluation",
"details"
] | [
0,
0,
0,
0
] |
246 | [
"Additionally,",
"on-policy",
"versus",
"off-policy",
"scores",
"split",
"per",
"sampling",
"procedure",
"are",
"displayed",
"in",
"table",
"12:",
"unsurprisingly,",
"greedy",
"decoding",
"for",
"TrufLLoff",
"outperforms",
"the",
"two",
"sampling-based",
"methods,",
"that",
"are",
"more",
"penalized",
"by",
"the",
"imperfect",
"generalization",
"of",
"the",
"optimized",
"policy",
"over",
"the",
"full",
"vocabulary."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
247 | [
"Note",
"that",
"for",
"VQAv2,",
"the",
"poor",
"performances",
"of",
"TrufLLoff,KL",
"on",
"the",
"external",
"LM",
"is",
"mainly",
"due",
"to",
"numerical",
"instability",
"challenges",
"when",
"using",
"GPT-2",
"as",
"the",
"target",
"policy",
"of",
"the",
"KL",
"regularization",
"term."
] | [
0,
0,
0,
13,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
248 | [
"Yet,",
"keeping",
"truncation",
"at",
"test",
"time",
"remains",
"crucial",
"with",
"large",
"vocabulary."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
249 | [
"In",
"such",
"a",
"setting,",
"it",
"hence",
"improves",
"the",
"global",
"scores",
"of",
"the",
"off-policy",
"version",
"of",
"TrufLL,",
"and",
"enables",
"a",
"much",
"better",
"generalization",
"at",
"test",
"time",
"of",
"the",
"global",
"policy",
"over",
"the",
"full",
"vocabulary."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
250 | [
"Interestingly,",
"while",
"on",
"CLEVR,",
"TrufLLoff,KL",
"trades",
"off",
"task",
"performance",
"for",
"language",
"quality",
"when",
"compared",
"to",
"TrufLLoff,",
"on",
"VQAv2,",
"it",
"mainly",
"provides",
"a",
"better",
"learning",
"signal",
"for",
"the",
"complete",
"(large)",
"vocabulary."
] | [
0,
0,
0,
13,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
13,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
251 | [
"Indeed,",
"on",
"the",
"off-policy",
"setting",
"for",
"such",
"a",
"task,",
"the",
"exploding",
"values",
"for",
"e-ppl",
"suggest",
"that",
"the",
"optimized",
"language",
"agent",
"samples",
"incoherent",
"words",
"taken",
"outside",
"the",
"truncated",
"action",
"space,",
"as",
"corroborated",
"by",
"the",
"low",
"values",
"of",
"the",
"sumVA",
"ratio."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
7,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
7,
0
] |
252 | [
"The",
"full",
"results",
"emphasize",
"the",
"challenges",
"of",
"the",
"approach",
"for",
"the",
"large",
"vocabulary",
"of",
"VQAv2."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
13
] |
253 | [
"Table",
"11",
"displays",
"the",
"full",
"results",
"of",
"on-policy",
"versus",
"off-policy",
"scores",
"for",
"TrufLL",
"(Task-LM)",
"and",
"TrufLL",
"(Ext-LM)",
"on",
"the",
"two",
"tasks."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
2,
0,
1,
2,
0,
0,
0,
0
] |
254 | [
"Intuitively,",
"it",
"encourages",
"the",
"policy",
"to",
"stay",
"close",
"to",
"the",
"language",
"model’s",
"distribution,",
"with",
"a",
"distribution",
"support",
"attributing",
"negligible",
"probabilities",
"to",
"words",
"outside",
"the",
"truncated",
"action",
"space."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
255 | [
"Wu",
"et",
"al.,",
"2019),",
"and",
"refer",
"to",
"it",
"as",
"TrufLLoff,KL."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
1
] |
256 | [
"To",
"ease",
"off-policy",
"learning,",
"we",
"propose",
"to",
"add",
"a",
"KLregularization",
"term",
"in",
"the",
"RL",
"loss",
"(Jaques",
"et",
"al.,",
"2017,",
"2019;"
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
257 | [
"On-policy",
"TrufLL",
"versus",
"off-policy",
"TrufLL."
] | [
1,
2,
0,
1,
2
] |
258 | [
"This",
"suggests",
"that",
"on",
"a",
"large",
"vocabulary",
"task,",
"the",
"language",
"distribution",
"learned",
"by",
"the",
"SL",
"pretrained",
"policy",
"is",
"significantly",
"different",
"from",
"the",
"one",
"learned",
"with",
"TrufLL."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1
] |
259 | [
"In",
"table",
"10,",
"while",
"on",
"CLEVR,",
"TrufLLpretrain",
"marginally",
"improves",
"the",
"results",
"of",
"the",
"pretrain+RL",
"fine-tune",
"baseline,",
"the",
"combination",
"of",
"TrufLL",
"with",
"a",
"pre-training",
"phase",
"leads",
"to",
"performance",
"degradation",
"on",
"VQAv2."
] | [
0,
0,
0,
0,
0,
13,
1,
0,
0,
0,
0,
0,
0,
1,
2,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
13
] |
260 | [
"Therefore,",
"when",
"using",
"the",
"task-related",
"dataset,",
"we",
"evaluate",
"TrufLL",
"from",
"a",
"pretrained",
"policy,",
"and",
"we",
"refer",
"to",
"it",
"as",
"TrufLLpretrain."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1
] |
261 | [
"Although",
"TrufLL",
"aims",
"at",
"providing",
"a",
"robust",
"method",
"to",
"learn",
"a",
"language",
"model",
"(almost)",
"from",
"scratch,",
"we",
"investigate",
"whether",
"such",
"algorithm",
"can",
"be",
"complementary",
"to",
"RL",
"algorithms",
"with",
"a",
"pre-training",
"phase."
] | [
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
262 | [
"TrufLL",
"with",
"a",
"pre-training",
"phase."
] | [
1,
0,
0,
0,
0
] |
263 | [
"B.3",
"Additional",
"discussion"
] | [
0,
0,
0
] |
264 | [
"This",
"suggests",
"that",
"the",
"KL",
"regularization",
"term,",
"while",
"encouraging",
"the",
"policy",
"distribution",
"to",
"resemble",
"the",
"language",
"model",
"distribution,",
"fails",
"to",
"capture",
"the",
"task",
"pragmatics,",
"which",
"requires",
"generating",
"a",
"language",
"that",
"is",
"visually",
"grounded."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
265 | [
"On",
"the",
"other",
"hand,",
"the",
"scratch+KL",
"baselines",
"stay",
"stuck",
"to",
"a",
"low",
"training",
"return."
] | [
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0
] |
266 | [
"The",
"training",
"curves",
"of",
"TrufLL",
"present",
"a",
"steady",
"increase",
"in",
"the",
"return",
"until",
"reaching",
"convergence,",
"confirming",
"that",
"our",
"approach,",
"by",
"guiding",
"the",
"exploration",
"of",
"the",
"action",
"space,",
"provides",
"a",
"sufficient",
"learning",
"signal."
] | [
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
267 | [
"As",
"expected,",
"the",
"pretrain+RL",
"fine-tune",
"baseline",
"return",
"does",
"not",
"evolve",
"much,",
"confirming",
"that",
"the",
"policy",
"distribution",
"almost",
"does",
"not",
"shift",
"through",
"the",
"fine-tuning",
"phase."
] | [
0,
0,
0,
1,
2,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
268 | [
"Finally,",
"Figure",
"4",
"displays",
"the",
"evolution",
"of",
"the",
"training",
"return",
"for",
"TrufLL",
"and",
"the",
"baselines."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0
] |
269 | [
"The",
"former",
"displays",
"the",
"best",
"performance/language",
"scores",
"trade-off",
"for",
"the",
"schedule",
"\"τ:",
"3",
">",
"1.",
"&",
"Tu=5,000\",",
"while",
"the",
"latter",
"has",
"the",
"best",
"metrics",
"trade-off",
"for",
"\"τ:",
"1.5",
">",
"1.",
"&",
"Tu=5,000\"."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
5,
6,
6,
0,
3,
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
5,
6,
6,
0,
3
] |
270 | [
"(Ext-LM)",
"benefit",
"slightly",
"from",
"truncation",
"with",
"a",
"temperature",
"schedule",
"compared",
"to",
"a",
"vanilla",
"truncation."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
271 | [
"In",
"Table",
"9,",
"both",
"TrufLL",
"(Task-LM)",
"and",
"TrufLL"
] | [
0,
0,
0,
0,
1,
2,
0,
1
] |
272 | [
"While",
"temperature",
"scaling",
"(Bahdanau",
"et",
"al.,",
"2015)",
"is",
"usually",
"used",
"at",
"test",
"time",
"to",
"control",
"the",
"smoothness",
"of",
"the",
"language",
"model",
"distribution,",
"temperature",
"schedules",
"during",
"training",
"of",
"language",
"models",
"have",
"been",
"used",
"in",
"w<t)",
"distribution",
"is",
"several",
"settings",
"(Jang",
"et",
"al.,",
"2016;"
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
273 | [
"When",
"scaling",
"up",
"to",
"the",
"15k",
"words",
"of",
"the",
"VQAv2",
"task,",
"we",
"also",
"dynamically",
"decrease",
"the",
"truncation",
"size",
"through",
"training,",
"by",
"applying",
"a",
"decreasing",
"temperature",
"schedule",
"on",
"the",
"language",
"model."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
13,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
274 | [
"Temperature",
"scheduling:",
"On",
"the",
"CLEVR",
"task,",
"we",
"observed",
"that",
"dynamic",
"truncations",
"outperform",
"static",
"ones",
"such",
"as",
"top(k):",
"indeed,",
"they",
"better",
"take",
"into",
"account",
"the",
"inherent",
"variability",
"of",
"the",
"language",
"structure",
"at",
"the",
"sentence-level."
] | [
0,
0,
0,
0,
13,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
275 | [
"Table",
"6:",
"CLEVR",
"task:",
"Ablation",
"on",
"the",
"truncation",
"functions",
"with",
"parameters",
"sweep."
] | [
0,
0,
13,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
276 | [
"This",
"illustrates",
"that",
"using",
"a",
"language",
"similarity",
"score",
"as",
"a",
"reward",
"signal",
"is",
"much",
"less",
"interesting",
"than",
"a",
"reward",
"based",
"on",
"a",
"task",
"completion",
"score."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
277 | [
"While",
"on",
"such",
"a",
"task",
"TrufLL",
"still",
"exhibits",
"promising",
"language",
"scores,",
"the",
"n-grams",
"metrics",
"remain",
"lower",
"than",
"the",
"pretrained",
"baselines."
] | [
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
278 | [
"Finally,",
"Table",
"8",
"reports",
"CLEVR",
"metrics",
"when",
"using",
"the",
"BLEU",
"score",
"as",
"the",
"reward."
] | [
0,
0,
0,
0,
13,
0,
0,
0,
0,
7,
0,
0,
0,
0
] |
279 | [
"Such",
"an",
"ablation",
"presents",
"a",
"similar",
"pattern",
"than",
"VQAv2",
"results",
"described",
"in",
"section",
"5.2."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
13,
0,
0,
0,
0,
0
] |
280 | [
"Table",
"6",
"displays",
"the",
"complete",
"ablation",
"on",
"the",
"truncation",
"functions",
"with",
"parameters",
"sweep."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
281 | [
"B.1",
"CLEVR"
] | [
0,
13
] |
282 | [
"B",
"Additional",
"experiments"
] | [
0,
0,
0
] |
283 | [
"In",
"this",
"section,",
"we",
"detail",
"the",
"reward",
"function",
"used",
"for",
"the",
"VQAv2",
"task."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
13,
0
] |
284 | [
"A.5",
"Reward",
"formula",
"for",
"VQAv2"
] | [
0,
0,
0,
0,
13
] |
285 | [
"None,1,5,10,100",
",",
"bs",
"}"
] | [
5,
0,
3,
0
] |
286 | [
"0.01,",
"0.02,",
"0.05,",
"0.1",
",",
"ϵ",
"}",
"3,10−",
",",
"gradclip",
"}"
] | [
5,
5,
5,
5,
0,
3,
0,
0,
0,
3,
0
] |
287 | [
"following",
"values",
"were",
"tested:",
"β",
"3,5"
] | [
0,
0,
0,
0,
3,
5
] |
288 | [
"We",
"kept",
"the",
"network",
"size",
"giving",
"the",
"best",
"performances,",
"i.e.",
"policy",
"network",
"of",
"256",
"units",
"and",
"128",
"word",
"embedding",
"dimension."
] | [
0,
0,
0,
3,
4,
0,
0,
0,
0,
0,
0,
0,
0,
5,
3,
0,
5,
3,
4,
4
] |
289 | [
"}",
"Additionally,",
"we",
"also",
"tested",
"for",
"VQAv2",
"policy",
"networks",
"with",
"64,",
"256",
"and",
"1024",
"units,",
"with",
"respectively",
"32,",
"128",
"and",
"512",
"word",
"embedding",
"dimensions."
] | [
0,
0,
0,
0,
0,
0,
13,
0,
0,
0,
5,
5,
0,
5,
3,
0,
0,
5,
5,
0,
5,
3,
4,
4
] |
290 | [
"The",
"0.01,",
"0.02,",
"0.05,",
"0.1,",
"0.5,",
"0.9",
"lr",
",",
"}",
"10−",
"32,64,128",
"."
] | [
0,
5,
5,
5,
5,
5,
5,
3,
0,
0,
0,
5,
0
] |
291 | [
"Such",
"hyper-parameters",
"were",
"selected,",
"after",
"conducting",
"an",
"extensive",
"hyper-parameter",
"search."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |
292 | [
"5)",
"for",
"CLEVR",
"and",
"VQAv2."
] | [
5,
0,
13,
0,
13
] |
293 | [
"Finally,",
"for",
"the",
"RL",
"from",
"scratch",
"baselines,",
"we",
"perform",
"gradient",
"clipping",
"(gladclip)",
"of",
"1",
"(resp."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
4,
3,
0,
5,
0
] |
294 | [
"We",
"use",
"a",
"batch",
"size",
"(bs)",
"on",
"CLEVR",
"(resp.",
"VQAv2),",
"and",
"5",
"of",
"128",
"for",
"all",
"models",
"except",
"the",
"ones",
"with",
"KL",
"regularization,",
"for",
"which",
"we",
"use",
"a",
"batch",
"size",
"of",
"64."
] | [
0,
0,
0,
3,
4,
3,
0,
13,
0,
13,
0,
0,
0,
5,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
4,
0,
5
] |
295 | [
"We",
"use",
"Adam",
"optimizer",
"(Kingma",
"and",
"Ba,",
"2014)",
"with",
"a",
"learning",
"rate",
"6)",
"for",
"RL",
"algorithms",
"with",
"a",
"pre-training",
"phase",
"(lr)",
"of",
"10−",
"4",
"for",
"models",
"including",
"a",
"KL",
"regularization",
"term."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
4,
0,
0,
0,
0,
0,
0,
0,
0,
3,
0,
5,
6,
0,
0,
0,
0,
0,
0,
0
] |
296 | [
"VQAv2)."
] | [
13
] |
297 | [
"We",
"optimize",
"the",
"full",
"loss",
"L=LP",
"P",
"O",
"+αLV",
"F",
"+βLE",
"with",
"α=0.5,",
"β",
"=0.01",
"and",
"a",
"PPO",
"clipping",
"ratio",
"ϵ=0.02",
"(resp.",
"0.01)",
"for",
"CLEVR",
"(resp."
] | [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
3,
5,
0,
0,
0,
0,
0,
3,
0,
5,
0,
13,
0
] |
298 | [
"3",
"for",
"TrufLL",
"and",
"the",
"scratch",
"baseline,",
"10−"
] | [
0,
0,
1,
0,
0,
0,
0,
0
] |
299 | [
"For",
"VQAv2,",
"the",
"image",
"representation",
"is",
"the",
"average",
"of",
"200",
"bounding",
"box",
"features",
"of",
"dimension",
"1048,",
"extracted",
"from",
"a",
"faster",
"R-CNN",
"(Ren",
"et",
"al.,",
"2015)."
] | [
0,
13,
0,
0,
0,
0,
0,
0,
0,
5,
3,
4,
4,
0,
3,
5,
0,
0,
0,
0,
0,
0,
0,
0,
0
] |