1 citations · 1 across the 4 of their papers we have counts for
5 papers
ChemExplain: A Multimodal Benchmark for Explanatory Chemical Reasoning
Aotian Chen, Frazier N. Baker, Reza Averly +5
Current chemistry benchmarks primarily evaluate outcome prediction or reaction pathway generation, but rarely test whether a model can explain why an observed chemical effect occur…
The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy
Chunzheng Zhu, Lei Tian, Bohan Tan +15
The growing ability of large language models and vision-language models to jointly interpret and reason over images and text is reshaping medical imaging AI, moving it from task-sp…
Hierarchical Process Reward Models are Symbolic Vision Learners
Shan Zhang, Aotian Chen, Kai Zou +3
Symbolic computer vision represents diagrams through explicit logical rules and structured representations, enabling interpretable understanding in machine vision. This requires fu…
Math Blind: Failures in Diagram Understanding Undermine Reasoning in MLLMs
Yanpeng Sun, Shan Zhang, Wei Tang +5
Diagrams represent a form of visual language that encodes abstract concepts and relationships through structured symbols and their spatial arrangements. Unlike natural images, they…
Open Eyes, Then Reason: Fine-grained Visual Mathematical Understanding in MLLMs
Shan Zhang, Aotian Chen, Yanpeng Sun +6
Current multimodal large language models (MLLMs) often underperform on mathematical problem-solving tasks that require fine-grained visual understanding. The limitation is largely…