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cs.CL2025
Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling
Yimin Du
The quality of human preference data is crucial for training and evaluating large language models (LLMs), particularly in reinforcement learning from human feedback (RLHF) and dire…
cs.CL2025
Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond
Liang Wen, Yunke Cai, Fenrui Xiao +11
This paper introduces Light-R1, an open-source suite for training long reasoning models using reproducible and cost-effective methodology. Given the proprietary nature of data used…