作者位次 #6/8ICML 2026Poster· Deep Learning / Large Language Models
Reward Modeling from Natural Language Human Feedback
Zongqi Wang · Rui Wang · Yuchuan Wu · Yiyao Yu · Pinyi Zhang · Shaoning Sun · Yujiu Yang · Yongbin Li
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Zongqi Wang · Rui Wang · Yuchuan Wu · Yiyao Yu · Pinyi Zhang · Shaoning Sun · Yujiu Yang · Yongbin Li
Shaoning Sun · Mingzhu Cai · Huang He · Bingjin Chen · Siqi Bao · Yujiu Yang · hua wu · Haifeng Wang
Language model families exhibit striking disparity in their capacity to benefit from reinforcement learning: under identical training, models like Qwen achieve substantial gains, while others like Llama yield limited improvements. Complementing data-centric approaches, we reveal that this dispari...
Tao Liu · Taiqiang Wu · Runming Yang · Shaoning Sun · Junjie Wang · Yujiu Yang
Supervised fine-tuning (SFT) is a fundamental post-training strategy to align Large Language Models (LLMs) with human intent. However, traditional SFT often ignores the \textit{one-to-many} nature of language by forcing alignment with a single reference answer, leading to the model overfitting to...