activity
20242026
collaborators

5 papers

cs.AI2026

Improving Multimodal Reasoning via Worst Dimension Optimization

Haocheng Lv, Huaping Zhang, Qiuchi Li +2

Multimodal reasoning requires a path that retains integrity over a wide range of constraints, from visual grounding to logic consistency. However, the current Process Reward Models…

cs.CE2026

RefiningGPT: Specialized language Models for Automated Refinery Unit-level Process Diagram Synthesis

Dongxiao Liu, Yuwen Ding, Xinghai Wei +4

Applying LLMs to complex industrial processes remains challenging due to the semantic gap between natural language design intents and the rigorous physical logic of engineering. In…

cs.CL2026

Investigating Cross-Modal Skill Injection: Scenarios, Methods, and Hyperparameters

Zhiyu Xu, Lean Wang, Yuanxin Liu +5

Vision-Language Models (VLMs) have demonstrated remarkable proficiency in general multi-modal understanding; yet they struggle to efficiently acquire continually evolving domain-sp…

cs.CV2025

ProReason: Multi-Modal Proactive Reasoning with Decoupled Eyesight and Wisdom

Jingqi Zhou, Sheng Wang, Jingwei Dong +6

Large vision-language models (LVLMs) have witnessed significant progress on visual understanding tasks. However, they often prioritize language knowledge over image information on…

cs.CL2024

Understanding the Role of LLMs in Multimodal Evaluation Benchmarks

Botian Jiang, Lei Li, Xiaonan Li +5

The rapid advancement of Multimodal Large Language Models (MLLMs) has been accompanied by the development of various benchmarks to evaluate their capabilities. However, the true na…