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cs.CL2025
RewardAnything: Generalizable Principle-Following Reward Models
Zhuohao Yu, Jiali Zeng, Weizheng Gu +7
Reward Models, essential for guiding Large Language Model optimization, are typically trained on fixed preference datasets, resulting in rigid alignment to single, implicit prefere…
cs.CL2024
RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation
Xuanwang Zhang, Yunze Song, Yidong Wang +10
Large Language Models (LLMs) demonstrate human-level capabilities in dialogue, reasoning, and knowledge retention. However, even the most advanced LLMs face challenges such as hall…