4 papers · 1 filter
LGM: Enhancing Large Language Models with Conceptual Meta-Relations and Iterative Retrieval
Wenchang Lei, Ping Zou, Yue Wang +2
Large language models (LLMs) exhibit strong semantic understanding, yet struggle when user instructions involve ambiguous or conceptually misaligned terms. We propose the Language…
A Model Can Help Itself: Reward-Free Self-Training for LLM Reasoning
Mengqi Li, Lei Zhao, Anthony Man-Cho So +2
Can a language model improve reasoning by learning from its own imperfect responses, without rewards or teacher-provided solutions? We present Self-evolving Post-Training (SePT), a…
StreamBP: Memory-Efficient Exact Backpropagation for Long Sequence Training of LLMs
Qijun Luo, Mengqi Li, Lei Zhao +1
Training language models on long sequence data is a demanding requirement for enhancing the model's capability on complex tasks, e.g., long-chain reasoning. However, as the sequenc…
DPO-Shift: Shifting the Distribution of Direct Preference Optimization
Xiliang Yang, Feng Jiang, Qianen Zhang +2
Direct Preference Optimization (DPO) and its variants have become increasingly popular for aligning language models with human preferences. These methods aim to teach models to bet…