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Collections including paper arxiv:2505.16459
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MMRA: A Benchmark for Multi-granularity Multi-image Relational Association
Paper • 2407.17379 • Published • 3 -
MMSearch: Benchmarking the Potential of Large Models as Multi-modal Search Engines
Paper • 2409.12959 • Published • 38 -
MMMR: Benchmarking Massive Multi-Modal Reasoning Tasks
Paper • 2505.16459 • Published • 45 -
VideoReasonBench: Can MLLMs Perform Vision-Centric Complex Video Reasoning?
Paper • 2505.23359 • Published • 39
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Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model
Paper • 2407.07053 • Published • 47 -
LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models
Paper • 2407.12772 • Published • 35 -
VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models
Paper • 2407.11691 • Published • 15 -
MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models
Paper • 2408.02718 • Published • 62
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The Leaderboard Illusion
Paper • 2504.20879 • Published • 72 -
Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures
Paper • 2505.09343 • Published • 72 -
LLMs for Engineering: Teaching Models to Design High Powered Rockets
Paper • 2504.19394 • Published • 14 -
Generative AI for Character Animation: A Comprehensive Survey of Techniques, Applications, and Future Directions
Paper • 2504.19056 • Published • 18
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MLLM-as-a-Judge for Image Safety without Human Labeling
Paper • 2501.00192 • Published • 31 -
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 107 -
Xmodel-2 Technical Report
Paper • 2412.19638 • Published • 26 -
HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs
Paper • 2412.18925 • Published • 104
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 28 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
-
The Leaderboard Illusion
Paper • 2504.20879 • Published • 72 -
Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures
Paper • 2505.09343 • Published • 72 -
LLMs for Engineering: Teaching Models to Design High Powered Rockets
Paper • 2504.19394 • Published • 14 -
Generative AI for Character Animation: A Comprehensive Survey of Techniques, Applications, and Future Directions
Paper • 2504.19056 • Published • 18
-
MMRA: A Benchmark for Multi-granularity Multi-image Relational Association
Paper • 2407.17379 • Published • 3 -
MMSearch: Benchmarking the Potential of Large Models as Multi-modal Search Engines
Paper • 2409.12959 • Published • 38 -
MMMR: Benchmarking Massive Multi-Modal Reasoning Tasks
Paper • 2505.16459 • Published • 45 -
VideoReasonBench: Can MLLMs Perform Vision-Centric Complex Video Reasoning?
Paper • 2505.23359 • Published • 39
-
MLLM-as-a-Judge for Image Safety without Human Labeling
Paper • 2501.00192 • Published • 31 -
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 107 -
Xmodel-2 Technical Report
Paper • 2412.19638 • Published • 26 -
HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs
Paper • 2412.18925 • Published • 104
-
Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model
Paper • 2407.07053 • Published • 47 -
LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models
Paper • 2407.12772 • Published • 35 -
VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models
Paper • 2407.11691 • Published • 15 -
MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models
Paper • 2408.02718 • Published • 62
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 28 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 14 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23