Publications
A complete list of publications can be found on Google Scholar.
* denotes equal contribution.
2026
[arXiv] MemLife: Curating and Reasoning over Long-Term Egocentric Video Memories [Paper]
[NeurIPS] Rethinking Visual Attribution for Chest X-ray Reasoning in Large Vision Language Models [Paper] [Code]
[NeurIPS] CASL: Concept-Aligned Sparse Latents for Interpreting Diffusion Models [Paper]
[Nature Communications] Supervising the search process produces reliable and generalizable information-seeking agents [Paper] [Code] [Homepage]
[EMNLP] Triggering Chain-of-Thought via Latent Feature Interventions in Large Language Models [Paper] [Code]
[ECCV] Towards Robustness against Typographic Attack with Training-free Concept Localization [Paper] [Code]
[KDD] Concept-Residual Representation Expansion for Robustness to Spurious Correlations [Paper]
[CVPR] Retrieving Counterfactuals Improves Visual In-Context Learning [Paper] [Code] [Homepage]
[AISTATS] Neural Additive Experts: Context-Gated Experts for Controllable Model Additivity [Paper] [Code]
[Bioinformatics] Cell-o1: training LLMs to solve single-cell reasoning puzzles with reinforcement learning [Paper] [Code]
[ICLR] Toward Faithful Retrieval-Augmented Generation with Sparse Autoencoders [Paper] [Code] [Homepage]
[AAAI (Oral)] Concept-RuleNet: Grounded Multi-Agent Neurosymbolic Reasoning in Vision Language Models [Paper]
2025
[EMNLP] COCO-Tree: Compositional Hierarchical Concept Trees for Enhanced Reasoning in Vision Language Models [Paper] [Code]
[ICCV] GCAV: A Global Concept Activation Vector Framework for Cross-Layer Consistency in Interpretability [Paper] [Code]
[TKDD] ProtoNAM: Prototypical Neural Additive Models for Interpretable Deep Tabular Learning [Paper] [Code]
[IJCAI] Toward Reliable Scientific Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models [Paper] [Code]
[IJCAI] ASCENT-ViT: Attention-based Scale-aware Concept Learning Framework for Enhanced Alignment in Vision Transformers [Paper] [Code]
[KDD] IdeaBench: Benchmarking Large Language Models for Research Idea Generation [Paper]
[ACL (Findings)] MedCite: Can Language Models Generate Verifiable Text for Medicine? [Paper]
[PSB] Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions [Paper] [Code]
2024
[NeurIPS (Oral)] MedCalc-Bench: Evaluating Large Language Models for Medical Calculations [Paper] [Code]
[KDD] CoLiDR: Concept Learning using Aggregated Disentangled Representations [Paper]
[ACL (Findings)] Benchmarking retrieval-augmented generation for medicine [Paper] [Code] [Homepage]
[IJCAI] A Self-explaining Neural Architecture for Generalizable Concept Learning [Paper]
[Bioinformatics] DeepGSEA: Explainable Deep Gene Set Enrichment Analysis for Single-cell Transcriptomic Data [Paper] [Code]
2023
[Bioinformatics] ProtoCell4P: an explainable prototype-based neural network for patient classification using single-cell RNA-seq [Paper] [Code]
2022
[ACM Computing Surveys] Biomedical question answering: a survey of approaches and challenges [Paper]