63 citations · 239 across the 76 of their papers we have counts for
13 papers · 1 filter
EEGBind: Detecting Source-Level Interictal Epileptiform Discharges via EEG-Centric Multimodal Binding
Muchen Li, Anglin Liu, Xuetian Gao +2
Source-level analysis of interictal epileptiform discharges (IEDs) is relevant to presurgical evaluation and treatment planning because it helps characterize where epileptiform act…
Coupled Graph--Policy Distillation for Personalized Medication Safety in Older Adults with Multimorbidity
Zihan Wang, Anglin Liu, Rongyi Wang +6
Large language model (LLM) agents can support medication review between clinical visits, but safe choices for older adults with multimorbidity depend on conditions, medications, an…
PATH: Next-Interval Prediction via Autoregressive Tree Hierarchy on Tabular Data
Pengxiang Cai, Wanchen Lian, Chenyang Liu +4
Interval prediction aims to achieve a target coverage level while producing intervals that are as short as possible. Many conformal regression pipelines first predict an uncertaint…
JustLLMGRPO: Radiographic Control for Chest X-Ray Generation
Pengxiang Cai, Xiaohan Li, Anglin Liu +3
Text-conditioned chest X-ray generation aims to synthesize realistic radiographs that faithfully depict specified findings. Existing work has primarily improved quality by updating…
Decoding Children's Gait Behavior
Yifan Shen, Boyi Li, Meihuan Huang +12
We introduce a new problem domain for human action recognition: the fine-grained analysis of children's gait behaviors from standard RGB video. We specifically target the ambulator…
Geometric Gradient Rectification for Safe Open-Set Semi-Supervised Learning
Jiahe Chen, Qian Shao, Qiyuan Chen +4
Open-set semi-supervised learning aims to leverage unlabeled data that may contain out-of-distribution outliers while maintaining performance on in-distribution classes. Existing m…
Curriculum Reinforcement Learning Can Incentivize Reasoning Capacity in LLMs Beyond the Base Model
Pengxiang Cai, Tianchen Fang, Xiaohan Li +3
Reinforcement learning with verifiable rewards (RLVR) is widely viewed as a promising path toward continuously improving large language models. Recent works, however, suggest that…
APCyc: Property-Informed Design of Cyclic Peptides via Automated Cyclization
Yifan Zhao, Lang Qin, Jintai Chen
Cyclic peptides represent a promising class of therapeutic compounds in modern drug discovery, often offering improved stability and binding affinity. However, the de novo design o…
Can Broad Biomedical Knowledge be Contextualized into Scenario-Grounded Propositions?
Qingyuan Zeng, Ziyang Chen, Pengxiang Cai +5
Biomedical discovery often requires connecting broad biomedical knowledge with specific experimental or clinical data. Background knowledge suggests relevant mechanisms but is usua…
Don't Retrain, Just Reuse: Recovering Dual-Target Molecules from Single-Target Diffusion Models
Qingyuan Zeng, Pengxiang Cai, Zixin Guan +4
Designing a single molecule that modulates two targets is a promising strategy for polypharmacology, but it remains substantially harder than standard single-target generation beca…
Learning What Matters: Dynamic Dimension Selection and Aggregation for Interpretable Vision-Language Reward Modeling
Qiyuan Chen, Hongsen Huang, Jiahe Chen +6
Vision-language reward modeling faces a dilemma: generative approaches are interpretable but slow, while discriminative ones are efficient but act as opaque "black boxes." To bridg…
Med-Scout: Curing MLLMs' Geometric Blindness in Medical Perception via Geometry-Aware RL Post-Training
Anglin Liu, Ruichao Chen, Yi Lu +2
Despite recent Multimodal Large Language Models (MLLMs)' linguistic prowess in medical diagnosis, we find even state-of-the-art MLLMs suffer from a critical perceptual deficit: geo…
ClinicalReTrial: Clinical Trial Redesign with Self-Evolving Agents
Sixue Xing, Kerui Wu, Xuanye Xia +4
Clinical trials constitute a critical yet exceptionally challenging and costly stage of drug development ($2.6B per drug), where protocols are encoded as complex natural language…