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Collections including paper arxiv:2501.16411
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PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understanding
Paper • 2501.16411 • Published • 18 -
Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 26 -
Return of the Encoder: Maximizing Parameter Efficiency for SLMs
Paper • 2501.16273 • Published • 5
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Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model
Paper • 2407.07053 • Published • 44 -
LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models
Paper • 2407.12772 • Published • 34 -
VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models
Paper • 2407.11691 • Published • 14 -
MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models
Paper • 2408.02718 • Published • 61
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GAIA: a benchmark for General AI Assistants
Paper • 2311.12983 • Published • 192 -
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
Paper • 2311.16502 • Published • 35 -
BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 26 -
RULER: What's the Real Context Size of Your Long-Context Language Models?
Paper • 2404.06654 • Published • 35