1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.AI2026
ShapE-GRPO: Shapley-Enhanced Reward Allocation for Multi-Candidate LLM Training
Rui Ai, Yu Pan, David Simchi-Levi +1
In user-agent interaction scenarios such as recommendation, brainstorming, and code suggestion, Large Language Models (LLMs) often generate sets of candidate recommendations where…
cs.LG2025★ 1 cited
What Matters in Data for DPO?
Yu Pan, Zhongze Cai, Guanting Chen +2
Direct Preference Optimization (DPO) has emerged as a simple and effective approach for aligning large language models (LLMs) with human preferences, bypassing the need for a learn…
cs.LG2025
Understanding the Impact of Sampling Quality in Direct Preference Optimization
Kyung Rok Kim, Yumo Bai, Chonghuan Wang +1
We study how data of higher quality can be leveraged to improve performance in Direct Preference Optimization (DPO), aiming to understand its impact on DPO training dynamics. Our a…