collaborators

15 papers

cs.CV2026

When Cultures Move: Measuring and Improving Multicultural Text-to-Video Generation

Shuowei Li, Yuming Zhao, Parth Bhalerao +1

Text-to-video (T2V) generation has rapidly progressed in visual fidelity, yet its ability to faithfully represent multiple cultures within a single prompt remains underexplored. We…

cs.AI2026

Entropy Is Not Enough: Unlocking Effective Reinforcement Learning for Visual Reasoning via Vision-Anchored Token Selection

Senjie Jin, Peixin Wang, Boyang Liu +8

While token-level entropy is commonly recognized as effective for credit assignment in text-only reinforcement learning with verifiable rewards (RLVR), it remains unclear whether t…

cs.AI2026

Active Evidence-Seeking and Diagnostic Reasoning in Large Language Models for Clinical Decision Support

Chen Zhan, Xihe Qiu, Xiaoyu Tan +8

Large language models perform well on static medical examinations, yet clinical diagnosis often requires iterative evidence gathering under uncertainty. Building on prior interacti…

cs.LG2026

ReCrit: Transition-Aware Reinforcement Learning for Scientific Critic Reasoning

Wanghan Xu, Yuhao Zhou, Hengyuan Zhao +8

Large language models can fail in critic interaction not only by answering incorrectly, but also by abandoning an initially correct scientific solution after user criticism. This i…

cs.CL2026

How Large Language Models Balance Internal Knowledge with User and Document Assertions

Shuowei Li, Haoxin Li, Wenda Chu +1

Large language models (LLMs) often need to balance their internal parametric knowledge with external information, such as user beliefs and content from retrieved documents, in real…

cs.LG2026

Conditional Factuality Controlled LLMs with Generalization Certificates via Conformal Sampling

Kai Ye, Qingtao Pan, Shuo Li

Large language models (LLMs) need reliable test-time control of hallucinations. Existing conformal methods for LLMs typically provide only \emph{marginal} guarantees and rely on a…