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Collections including paper arxiv:2408.13257

Multimodal Benchmarks

Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model

Paper • 2407.07053 • Published Jul 9 • 41
LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

Paper • 2407.12772 • Published Jul 17 • 33
VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models

Paper • 2407.11691 • Published Jul 16 • 13
MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models

Paper • 2408.02718 • Published Aug 5 • 60

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

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

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

Paper • 2402.04615 • Published Feb 7 • 38
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7 • 19

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?

Paper • 2408.13257 • Published Aug 23 • 25
yifanzhang114/MME-RealWorld

Preview • Updated Sep 18 • 306 • 12

Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?

Paper • 2408.13257 • Published Aug 23 • 25
yifanzhang114/MME-RealWorld

Preview • Updated Sep 18 • 306 • 12
yifanzhang114/MME-RealWorld-Base64

Viewer • Updated Sep 27 • 11.5k • 275 • 1
yifanzhang114/MME-RealWorld-CN-Lmms-eval

Viewer • Updated Sep 21 • 5.89k • 335 • 1

Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs

Paper • 2406.16860 • Published Jun 24 • 57
Understanding Alignment in Multimodal LLMs: A Comprehensive Study

Paper • 2407.02477 • Published Jul 2 • 21
LongVILA: Scaling Long-Context Visual Language Models for Long Videos

Paper • 2408.10188 • Published Aug 19 • 51
Building and better understanding vision-language models: insights and future directions

Paper • 2408.12637 • Published Aug 22 • 117

CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data

Paper • 2404.15653 • Published Apr 24 • 26
MoDE: CLIP Data Experts via Clustering

Paper • 2404.16030 • Published Apr 24 • 12
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning

Paper • 2405.12130 • Published May 20 • 45
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention

Paper • 2405.12981 • Published May 21 • 28

Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset

Paper • 2403.09029 • Published Mar 14 • 54
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression

Paper • 2403.12968 • Published Mar 19 • 24
RAFT: Adapting Language Model to Domain Specific RAG

Paper • 2403.10131 • Published Mar 15 • 67
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking

Paper • 2403.09629 • Published Mar 14 • 72

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