Biomedical Question Answering: A Comprehensive Review. - Qiao Jin 001; Zheng Yuan 002; Guangzhi Xiong; Qianlan Yu; Chuanqi Tan; Mosha Chen; Songfang Huang; Xiaozhong Liu; Sheng Yu 002 (CoRR, 2021)

Biomedical Question Answering: A Survey of Approaches and Challenges. - Qiao Jin 001; Zheng Yuan 002; Guangzhi Xiong; Qianlan Yu; Huaiyuan Ying; Chuanqi Tan; Mosha Chen; Songfang Huang; Xiaozhong Liu; Sheng Yu 002 (ACM Comput. Surv., 2023)

ProtoCell4P: an explainable prototype-based neural network for patient classification using single-cell RNA-seq. - Guangzhi Xiong; Stefan Bekiranov; Aidong Zhang (Bioinform., 2023)

Benchmarking Retrieval-Augmented Generation for Medicine. - Guangzhi Xiong; Qiao Jin 001; Zhiyong Lu; Aidong Zhang (ACL (Findings), 2024)

Embracing Foundation Models for Advancing Scientific Discovery. - Sikun Guo; Amir Hassan Shariatmadari; Guangzhi Xiong; Aidong Zhang (IEEE Big Data, 2024)

A Self-explaining Neural Architecture for Generalizable Concept Learning. - Sanchit Sinha; Guangzhi Xiong; Aidong Zhang (IJCAI, 2024)

CoLiDR: Concept Learning using Aggregated Disentangled Representations. - Sanchit Sinha; Guangzhi Xiong; Aidong Zhang (KDD, 2024)

MedCalc-Bench: Evaluating Large Language Models for Medical Calculations. - Nikhil Khandekar; Qiao Jin 001; Guangzhi Xiong; Soren Dunn; Serina S. Applebaum; Zain Anwar; Maame Sarfo-Gyamfi; Conrad W. Safranek; Abid A Anwar; Andrew Zhang; Aidan Gilson; Maxwell B. Singer; et al. (NeurIPS, 2024)

DeepGSEA: explainable deep gene set enrichment analysis for single-cell transcriptomic data. - Guangzhi Xiong; Nathan Leroy; Stefan Bekiranov; Nathan C. Sheffield; Aidong Zhang (Bioinform., 2024)

Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions. - Guangzhi Xiong; Qiao Jin 001; Xiao Wang; Minjia Zhang; Zhiyong Lu; Aidong Zhang (CoRR, 2024)

ProtoNAM: Prototypical Neural Additive Models for Interpretable Deep Tabular Learning. - Guangzhi Xiong; Sanchit Sinha; Aidong Zhang (CoRR, 2024)

Structural Causality-based Generalizable Concept Discovery Models. - Sanchit Sinha; Guangzhi Xiong; Aidong Zhang (CoRR, 2024)

Demystifying Large Language Models for Medicine: A Primer. - Qiao Jin 001; Nicholas Wan; Robert Leaman; Shubo Tian; Zhizheng Wang; Yifan Yang 006; Zifeng Wang 008; Guangzhi Xiong; Po-Ting Lai; Qingqing Zhu; Benjamin Hou; Maame Sarfo-Gyamfi; et al. (CoRR, 2024)

Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models. - Guangzhi Xiong; Eric Xie; Amir Hassan Shariatmadari; Sikun Guo; Stefan Bekiranov; Aidong Zhang (CoRR, 2024)

IdeaBench: Benchmarking Large Language Models for Research Idea Generation. - Sikun Guo; Amir Hassan Shariatmadari; Guangzhi Xiong; Albert Huang; Eric Xie; Stefan Bekiranov; Aidong Zhang (CoRR, 2024)

Humans Continue to Outperform Large Language Models in Complex Clinical Decision-Making: A Study with Medical Calculators. - Nicholas Wan; Qiao Jin 001; Joey Chan; Guangzhi Xiong; Serina S. Applebaum; Aidan Gilson; Reid McMurry; R. Andrew Taylor; Aidong Zhang; Qingyu Chen 001; Zhiyong Lu (CoRR, 2024)

Ensuring Safety and Trust: Analyzing the Risks of Large Language Models in Medicine. - Yifan Yang 006; Qiao Jin 001; Robert Leaman; Xiaoyu Liu 003; Guangzhi Xiong; Maame Sarfo-Gyamfi; Changlin Gong; Santiago Ferrière-Steinert; W. John Wilbur; Xiaojun Li; Jiaxin Yuan; Bang An 001; et al. (CoRR, 2024)

MedCite: Can Language Models Generate Verifiable Text for Medicine? - Xiao Wang; Mengjue Tan; Qiao Jin 001; Guangzhi Xiong; Yu Hu; Aidong Zhang; Zhiyong Lu; Minjia Zhang (ACL (Findings), 2025)

Optimizing External and Internal Knowledge of Foundation Models for Scientific Discovery. - Sikun Guo; Guangzhi Xiong; Aidong Zhang (SDM, 2025)

Leveraging Scale-aware Representations for improved Concept-Representation Alignment in ViTs. - Sanchit Sinha; Guangzhi Xiong; Aidong Zhang (CoRR, 2025)

RAG-Gym: Optimizing Reasoning and Search Agents with Process Supervision. - Guangzhi Xiong; Qiao Jin 001; Xiao Wang; Yin Fang; Haolin Liu; Yifan Yang 006; Fangyuan Chen; Zhixing Song; Dengyu Wang; Minjia Zhang; Zhiyong Lu; Aidong Zhang (CoRR, 2025)

Toward Reliable Biomedical Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models. - Guangzhi Xiong; Eric Xie; Corey Williams; Myles Kim; Amir Hassan Shariatmadari; Sikun Guo; Stefan Bekiranov; Aidong Zhang (CoRR, 2025)

Cell-o1: Training LLMs to Solve Single-Cell Reasoning Puzzles with Reinforcement Learning. - Yin Fang; Qiao Jin 001; Guangzhi Xiong; Bowen Jin; Xianrui Zhong; Siru Ouyang; Aidong Zhang; Jiawei Han 001; Zhiyong Lu (CoRR, 2025)