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cs.CL2025
Towards Effective Model Editing for LLM Personalization
Baixiang Huang, Limeng Cui, Jiapeng Liu +7
Personalization is becoming indispensable for LLMs to align with individual user preferences and needs. Yet current approaches are often computationally expensive, data-intensive,…
cs.LG2025
Towards Revealing the Effectiveness of Small-Scale Fine-tuning in R1-style Reinforcement Learning
Yutong Chen, Jiandong Gao, Ji Wu
R1-style Reinforcement Learning (RL) significantly enhances Large Language Models' reasoning capabilities, yet the mechanism behind rule-based RL remains unclear. We found that sma…