most citedUncertainty-Aware Large Language Models for Explainable Disease Diagnosis

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Enhancing User Engagement in Socially-Driven Dialogue through Interactive LLM Alignments

Jiashuo Wang, Kaitao Song, Chunpu Xu +5

Enhancing user engagement through interactions plays an essential role in socially-driven dialogues. While prior works have optimized models to reason over relevant knowledge or pl…

cs.CL2025

SPA-RL: Reinforcing LLM Agents via Stepwise Progress Attribution

Hanlin Wang, Chak Tou Leong, Jiashuo Wang +2

Reinforcement learning (RL) holds significant promise for training LLM agents to handle complex, goal-oriented tasks that require multi-step interactions with external environments…

cs.CL20251 cited

Uncertainty-Aware Large Language Models for Explainable Disease Diagnosis

Shuang Zhou, Jiashuo Wang, Zidu Xu +11

Explainable disease diagnosis, which leverages patient information (e.g., signs and symptoms) and computational models to generate probable diagnoses and reasonings, offers clear c…

q-bio.BM2025

PharMolixFM: All-Atom Foundation Models for Molecular Modeling and Generation

Yizhen Luo, Jiashuo Wang, Siqi Fan +1

Structural biology relies on accurate three-dimensional biomolecular structures to advance our understanding of biological functions, disease mechanisms, and therapeutics. While re…

cs.CL2023

Self-Detoxifying Language Models via Toxification Reversal

Chak Tou Leong, Yi Cheng, Jiashuo Wang +2

Language model detoxification aims to minimize the risk of generating offensive or harmful content in pretrained language models (PLMs) for safer deployment. Existing methods can b…