TraceAV-Bench is the first benchmark for multi-hop trajectory reasoning over long audio-visual videos, showing top models reach only 51-68% accuracy with substantial room for improvement.
Mathscape: Evaluating mllms in multimodal math scenarios through a hierarchical benchmark
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ErrorRadar is a new benchmark of 2,500 multimodal K-12 math problems for MLLM error step identification and categorization, where GPT-4o trails human experts by ~10%.
Reinforcement learning with three causal constraints enables multimodal models to internalize diagram-reasoning links in geometry, unlike SFT which only mimics surface format and harms performance.
citing papers explorer
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TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videos
TraceAV-Bench is the first benchmark for multi-hop trajectory reasoning over long audio-visual videos, showing top models reach only 51-68% accuracy with substantial room for improvement.
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ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection
ErrorRadar is a new benchmark of 2,500 multimodal K-12 math problems for MLLM error step identification and categorization, where GPT-4o trails human experts by ~10%.
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How RL Unlocks the Aha Moment in Geometric Interleaved Reasoning
Reinforcement learning with three causal constraints enables multimodal models to internalize diagram-reasoning links in geometry, unlike SFT which only mimics surface format and harms performance.
- OpenWorldLib: A Unified Codebase and Definition of Advanced World Models