5 papers
Diagram-MMU: A Multi-Modal Benchmark for Scientific Diagrams
Weihao Bo, Shan Zhang, Yanpeng Sun +7
Multimodal Large Language Models (MLLMs) have been growing the capability for scientific writing and collaboration. For example, OpenAI Prism is a free workspace for scientific wri…
PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization
Yao Ni, Shan Zhang, Piotr Koniusz
Parameter-Efficient Fine-Tuning (PEFT) effectively adapts pre-trained transformers to downstream tasks. However, the optimization of tasks performance often comes at the cost of ge…
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…
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…
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…