26 papers
The Personalization Mirage: How LLMs Fabricate User Profiles, and Why Self-Monitoring Misleads
Yushi Sun, Yanjie Zhang, Rui Sheng
Personalized LLMs with persistent memory are increasingly deployed, yet the faithfulness of their user models remains unexamined. We study over-inference (OI): the phenomenon where…
TACT: Taxonomy-Aligned Post-Training for Pedagogically Adaptive English Tutoring
Dongjie Yang, Siyan Lin, Leixian Shen +3
Large language models (LLMs) are increasingly used to provide conversational practice for English-as-a-second-language (ESL) learners. Effective ESL tutoring, however, requires mor…
CellPrism: A Visual Analytics System for Exploring AI-Driven Virtual Cells in Drug Discovery
Chuhan Shi, Zijian Guo, Zelin Zang +3
Gene perturbation analysis plays a critical role in drug discovery by enabling researchers to investigate how interventions on specific genes influence global gene expression patte…
MolecularCanvas: LLM-assisted Small-Molecule Drug Discovery via Structure-Guided Constraints
Haoyu Dong, Rui Sheng, Shuhao Zhang +7
Small-molecule drug discovery relies on iterative molecular optimization, where chemists repeatedly modify candidate compounds to balance multiple competing properties such as effi…
Fewer Clarifications, Better Code: Benchmarking Cross-Session Personalized Ambiguity Adaptation in Coding Assistants
Zijian Xu, Wenshuo Zhang, Zisen Qin +4
The paper defines personalized ambiguity adaptation for coding assistants, introduces the CAPA benchmark to evaluate how well models use a user's past resolved sessions to handle r…
Navigating the Mirage: A Dual-Path Agentic Framework for Robust Misleading Chart Question Answering
Yanjie Zhang, Yafei Li, Rui Sheng +5
The paper introduces ChartCynics, a dual‑path system that separates visual perception and data verification to detect misleading information in charts, using a skeptical reasoning…