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Collections including paper arxiv:2412.15213

Paper - Multimodal

Paper related to Multimodal Model - Research for a : Modular, Multimodal, Multi-Stream, Mixture of Expert, Universal Transformer, Matryoshka embedding

Flowing from Words to Pixels: A Framework for Cross-Modality Evolution

Paper • 2412.15213 • Published 14 days ago • 25
No More Adam: Learning Rate Scaling at Initialization is All You Need

Paper • 2412.11768 • Published 17 days ago • 41
Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference

Paper • 2412.13663 • Published 15 days ago • 115
Autoregressive Video Generation without Vector Quantization

Paper • 2412.14169 • Published 15 days ago • 14

Image Generation

Image Generation

Causal Diffusion Transformers for Generative Modeling

Paper • 2412.12095 • Published 17 days ago • 23
SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training

Paper • 2412.09619 • Published 21 days ago • 20
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation

Paper • 2412.07589 • Published 23 days ago • 46
Flowing from Words to Pixels: A Framework for Cross-Modality Evolution

Paper • 2412.15213 • Published 14 days ago • 25

Gen AI Diffusion

Animate-X: Universal Character Image Animation with Enhanced Motion Representation

Paper • 2410.10306 • Published Oct 14, 2024 • 54
ReCapture: Generative Video Camera Controls for User-Provided Videos using Masked Video Fine-Tuning

Paper • 2411.05003 • Published Nov 7, 2024 • 70
TIP-I2V: A Million-Scale Real Text and Image Prompt Dataset for Image-to-Video Generation

Paper • 2411.04709 • Published Nov 5, 2024 • 25
IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation

Paper • 2410.07171 • Published Oct 9, 2024 • 41

Perception and abstraction. Each modality is tokenized and embedded into vectors for model to comprehend.

VILA^2: VILA Augmented VILA

Paper • 2407.17453 • Published Jul 24, 2024 • 39
Octopus v4: Graph of language models

Paper • 2404.19296 • Published Apr 30, 2024 • 116
Octo-planner: On-device Language Model for Planner-Action Agents

Paper • 2406.18082 • Published Jun 26, 2024 • 47
Dolphin: Long Context as a New Modality for Energy-Efficient On-Device Language Models

Paper • 2408.15518 • Published Aug 28, 2024 • 42

MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training

Paper • 2311.17049 • Published Nov 28, 2023 • 1
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Paper • 2405.04434 • Published May 7, 2024 • 14
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision

Paper • 2303.17376 • Published Mar 30, 2023
Sigmoid Loss for Language Image Pre-Training

Paper • 2303.15343 • Published Mar 27, 2023 • 5

about 3 hours ago

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 25
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 12
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 39
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 20

Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis

Paper • 2401.09048 • Published Jan 17, 2024 • 9
Improving fine-grained understanding in image-text pre-training

Paper • 2401.09865 • Published Jan 18, 2024 • 16
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Paper • 2401.10891 • Published Jan 19, 2024 • 60
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild

Paper • 2401.13627 • Published Jan 24, 2024 • 73

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