2 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
Rubric-Aware On-Policy Self-Distillation for LLM Personalization
Yilun Qiu, Xiaoyan Zhao, Chengbing Wang +6
LLM personalization aims to generate responses aligned with individual users' preferences and needs. User-specific rubrics make these expectations explicit, providing direct superv…
Preference-Aware Rubric Learning for Personalized Evaluation
Yilun Qiu, Xiaoyan Zhao, Yang Zhang +7
As Large Language Models (LLMs) evolve from general-purpose assistants to user-centric agents, personalization has become central to aligning model behavior with individual prefere…
USB-Rec: An Effective Framework for Improving Conversational Recommendation Capability of Large Language Model
Jianyu Wen, Jingyun Wang, Cilin Yan +3
Recently, Large Language Models (LLMs) have been widely employed in Conversational Recommender Systems (CRSs). Unlike traditional language model approaches that focus on training,…
Efficient and Accurate Prompt Optimization: the Benefit of Memory in Exemplar-Guided Reflection
Cilin Yan, Jingyun Wang, Lin Zhang +6
Automatic prompt engineering aims to enhance the generation quality of large language models (LLMs). Recent works utilize feedbacks generated from erroneous cases to guide the prom…