119 citations · 119 across the 5 of their papers we have counts for
5 papers
SCOPE: Compress Mathematical Reasoning Steps for Efficient Automated Process Annotation
Huimin Xu, Xin Mao, Feng-Lin Li +4
Process Reward Models (PRMs) have demonstrated promising results in mathematical reasoning, but existing process annotation approaches, whether through human annotations or Monte C…
Full-Step-DPO: Self-Supervised Preference Optimization with Step-wise Rewards for Mathematical Reasoning
Huimin Xu, Xin Mao, Feng-Lin Li +4
Direct Preference Optimization (DPO) often struggles with long-chain mathematical reasoning. Existing approaches, such as Step-DPO, typically improve this by focusing on the first…
As Simple as Fine-tuning: LLM Alignment via Bidirectional Negative Feedback Loss
Xin Mao, Feng-Lin Li, Huimin Xu +3
Direct Preference Optimization (DPO) has emerged as a more computationally efficient alternative to Reinforcement Learning from Human Feedback (RLHF) with Proximal Policy Optimizat…
Don't Forget Your Reward Values: Language Model Alignment via Value-based Calibration
Xin Mao, Feng-Lin Li, Huimin Xu +2
While Reinforcement Learning from Human Feedback (RLHF) significantly enhances the generation quality of Large Language Models (LLMs), recent studies have raised concerns regarding…
Relational Reflection Entity Alignment
Xin Mao, Wenting Wang, Huimin Xu +2
Entity alignment aims to identify equivalent entity pairs from different Knowledge Graphs (KGs), which is essential in integrating multi-source KGs. Recently, with the introduction…