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cs.CL2025
Boosting Reward Model with Preference-Conditional Multi-Aspect Synthetic Data Generation
Jiaming Shen, Ran Xu, Yennie Jun +6
Reward models (RMs) are crucial for aligning large language models (LLMs) with human preferences. They are trained using preference datasets where each example consists of one inpu…
cs.CL2024
Integrating Planning into Single-Turn Long-Form Text Generation
Yi Liang, You Wu, Honglei Zhuang +8
Generating high-quality, in-depth textual documents, such as academic papers, news articles, Wikipedia entries, and books, remains a significant challenge for Large Language Models…