collaborators

13 papers

cs.IR2026

Uncertainty-aware Generative Recommendation

Chenxiao Fan, Chongming Gao, Yaxin Gong +3

Generative Recommendation has emerged as a transformative paradigm, reformulating recommendation as an end-to-end autoregressive sequence generation task. Despite its promise, exis…

cs.LG2026

Fine-grained List-wise Alignment for Generative Medication Recommendation

Chenxiao Fan, Chongming Gao, Wentao Shi +3

Accurate and safe medication recommendations are critical for effective clinical decision-making, especially in multimorbidity cases. However, existing systems rely on point-wise p…

cs.LG2026

Structured Scaling of AI Discovery Across Diverse Scientific Domains

Haotian Ye, Haowei Lin, Jingyi Tang +30

Scientific discovery often requires many cycles of proposing, testing, and refining candidate solutions. Language models can increasingly participate in these loops, but simply gen…

cs.CL2026

Medical Reasoning with Large Language Models: A Survey and MR-Bench

Xiaohan Ren, Chenxiao Fan, Wenyin Ma +4

Large language models (LLMs) have achieved strong performance on medical exam-style tasks, motivating growing interest in their deployment in real-world clinical settings. However,…

cs.CL2026

Don't Start Over: A Cost-Effective Framework for Migrating Personalized Prompts Between LLMs

Ziyi Zhao, Chongming Gao, Yang Zhang +5

Personalization in Large Language Models (LLMs) often relies on user-specific soft prompts. However, these prompts become obsolete when the foundation model is upgraded, necessitat…

cs.IR2025

MGFRec: Towards Reinforced Reasoning Recommendation with Multiple Groundings and Feedback

Shihao Cai, Chongming Gao, Haoyan Liu +4

The powerful reasoning and generative capabilities of large language models (LLMs) have inspired researchers to apply them to reasoning-based recommendation tasks, which require in…