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cs.LG2025
Logits-Based Finetuning
Jingyao Li, Senqiao Yang, Sitong Wu +4
In recent years, developing compact and efficient large language models (LLMs) has emerged as a thriving area of research. Traditional Supervised Fine-Tuning (SFT), which relies on…
cs.LG2025
Uni-DPO: A Unified Paradigm for Dynamic Preference Optimization of LLMs
Shangpin Peng, Weinong Wang, Zhuotao Tian +7
Direct Preference Optimization (DPO) has emerged as a cornerstone of reinforcement learning from human feedback (RLHF) due to its simplicity and efficiency. However, existing DPO-b…
cs.LG2024★ 1 cited
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Xin Lai, Zhuotao Tian, Yukang Chen +3
Mathematical reasoning presents a significant challenge for Large Language Models (LLMs) due to the extensive and precise chain of reasoning required for accuracy. Ensuring the cor…