collaborators

6 papers

cs.AI2026

CliniCARE-Bench: Clinical Calibrated Audit of Medical Reasoning in EHR

Veronica Chatrath, Bryan Zhu, George Pu +16

Large language models perform strongly on medical knowledge benchmarks, but reliable clinical deployment requires agents to conduct defensible investigations over heterogeneous, lo…

cs.AI2026

Agents' Last Exam

Yiyou Sun, Xinyang Han, Weichen Zhang +306

Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…

cs.CL2026

Diffusion-Inspired Masked Fine-Tuning for Knowledge Injection in Autoregressive LLMs

Xu Pan, Ely Hahami, Jingxuan Fan +2

Large language models (LLMs) are often used in environments where facts evolve, yet factual knowledge updates via fine-tuning on unstructured text often suffer from 1) reliance on…

cs.CL2026

User-Assistant Bias in LLMs

Xu Pan, Jingxuan Fan, Zidi Xiong +3

Modern large language models (LLMs) are typically trained and deployed using structured role tags (e.g. system, user, assistant, tool) that explicitly mark the source of each piece…

cs.AI2026

Circuit Mechanisms for Spatial Relation Generation in Diffusion Transformers

Binxu Wang, Jingxuan Fan, Xu Pan

Diffusion Transformers (DiTs) have greatly advanced text-to-image generation, but models still struggle to generate the correct spatial relations between objects as specified in th…

cs.LG2026

Scaling Reward Modeling without Human Supervision

Jingxuan Fan, Yueying Li, Zhenting Qi +4

Learning from feedback is an instrumental process for advancing the capabilities and safety of frontier models, yet its effectiveness is often constrained by cost and scalability.…