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cs.CL2025
JustRL: Scaling a 1.5B LLM with a Simple RL Recipe
Bingxiang He, Zekai Qu, Zeyuan Liu +9
Recent advances in reinforcement learning for large language models have converged on increasing complexity: multi-stage training pipelines, dynamic hyperparameter schedules, and c…
cs.CL2025
AIR: A Systematic Analysis of Annotations, Instructions, and Response Pairs in Preference Dataset
Bingxiang He, Wenbin Zhang, Jiaxi Song +11
Preference learning is critical for aligning large language models (LLMs) with human values, yet its success hinges on high-quality datasets comprising three core components: Prefe…
cs.CL2024
Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment
Yiju Guo, Ganqu Cui, Lifan Yuan +9
Alignment in artificial intelligence pursues the consistency between model responses and human preferences as well as values. In practice, the multifaceted nature of human preferen…