MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Models
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2502.00698
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Published
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24
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DeepRAG: Thinking to Retrieval Step by Step for Large Language Models
Paper • 2502.01142 • Published • 24 -
ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning
Paper • 2502.01100 • Published • 19 -
The Jumping Reasoning Curve? Tracking the Evolution of Reasoning Performance in GPT-[n] and o-[n] Models on Multimodal Puzzles
Paper • 2502.01081 • Published • 13 -
Improved Training Technique for Latent Consistency Models
Paper • 2502.01441 • Published • 8 -
PhD Knowledge Not Required: A Reasoning Challenge for Large Language Models
Paper • 2502.01584 • Published • 9 -
COCONut-PanCap: Joint Panoptic Segmentation and Grounded Captions for Fine-Grained Understanding and Generation
Paper • 2502.02589 • Published • 9 -
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models
Paper • 2502.03032 • Published • 60 -
Great Models Think Alike and this Undermines AI Oversight
Paper • 2502.04313 • Published • 33 -
Ola: Pushing the Frontiers of Omni-Modal Language Model with Progressive Modality Alignment
Paper • 2502.04328 • Published • 29 -
ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
Paper • 2502.04320 • Published • 36 -
BOLT: Bootstrap Long Chain-of-Thought in Language Models without Distillation
Paper • 2502.03860 • Published • 25