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From the 1 of 9 linked papers with an AI index.

collaborators

9 papers

cs.MM2026

ELF: A Family of Encoder-Free ECG-Language Models

William Han, Tony Chen, Chaojing Duan +6

The paper introduces ELF, a family of encoder‑free ECG‑language models that interpret electrocardiograms without relying on separate pretrained ECG encoders, achieving competitive…

cs.CV2025

Feature-EndoGaussian: Feature Distilled Gaussian Splatting in Surgical Deformable Scene Reconstruction

Kai Li, Junhao Wang, William Han +1

Minimally invasive surgery (MIS) requires high-fidelity, real-time visual feedback of dynamic and low-texture surgical scenes. To address these requirements, we introduce FeatureEn…

cs.LG2025

Behavior Injection: Preparing Language Models for Reinforcement Learning

Zhepeng Cen, Yihang Yao, William Han +2

Reinforcement learning (RL) has emerged as a powerful post-training technique to incentivize the reasoning ability of large language models (LLMs). However, LLMs can respond very i…

cs.CL2025

Retrieval-Augmented Generation for Electrocardiogram-Language Models

Xiaoyu Song, William Han, Tony Chen +4

Interest in generative Electrocardiogram-Language Models (ELMs) is growing, as they can produce textual responses conditioned on ECG signals and textual queries. Unlike traditional…

cs.CL2025

Safety is Not Only About Refusal: Reasoning-Enhanced Fine-tuning for Interpretable LLM Safety

Yuyou Zhang, Miao Li, William Han +3

Large Language Models (LLMs) are vulnerable to jailbreak attacks that exploit weaknesses in traditional safety alignment, which often relies on rigid refusal heuristics or represen…

cs.CL2025

ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling

William Han, Chaojing Duan, Michael A. Rosenberg +2

Large Language Models (LLMs) have demonstrated exceptional versatility across domains, including applications to electrocardiograms (ECGs). A growing body of work focuses on genera…