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cs.CL2025
Unintended Misalignment from Agentic Fine-Tuning: Risks and Mitigation
Dongyoon Hahm, Taywon Min, Woogyeol Jin +1
Beyond simple text generation, Large Language Models (LLMs) have evolved into agentic systems capable of planning and interacting with external tools to solve complex tasks. This e…
cs.AI2025★ 4 cited
Understanding Impact of Human Feedback via Influence Functions
Taywon Min, Haeone Lee, Yongchan Kwon +1
In Reinforcement Learning from Human Feedback (RLHF), it is crucial to learn suitable reward models from human feedback to align large language models (LLMs) with human intentions.…