1 citations · 2 across the 11 of their papers we have counts for
5 papers · 1 filter
Towards Proactive Personalization through Profile Customization for Individual Users in Dialogues
Xiaotian Zhang, Yuan Wang, Ruizhe Chen +3
The deployment of Large Language Models (LLMs) in interactive systems necessitates a deep alignment with the nuanced and dynamic preferences of individual users. Current alignment…
Beyond N-grams: A Hierarchical Reward Learning Framework for Clinically-Aware Medical Report Generation
Yuan Wang, Shujian Gao, Jiaxiang Liu +6
Automatic medical report generation can greatly reduce the workload of doctors, but it is often unreliable for real-world deployment. Current methods can write formally fluent sent…
Med-U1: Incentivizing Unified Medical Reasoning in LLMs via Large-scale Reinforcement Learning
Xiaotian Zhang, Yuan Wang, Zhaopeng Feng +6
Medical Question-Answering (QA) encompasses a broad spectrum of tasks, including multiple choice questions (MCQ), open-ended text generation, and complex computational reasoning. D…
Persona-judge: Personalized Alignment of Large Language Models via Token-level Self-judgment
Xiaotian Zhang, Ruizhe Chen, Yang Feng +1
Aligning language models with human preferences presents significant challenges, particularly in achieving personalization without incurring excessive computational costs. Existing…
DiffPO: Diffusion-styled Preference Optimization for Efficient Inference-Time Alignment of Large Language Models
Ruizhe Chen, Wenhao Chai, Zhifei Yang +5
Inference-time alignment provides an efficient alternative for aligning LLMs with humans. However, these approaches still face challenges, such as limited scalability due to policy…