Be Careful When Fine-tuning On Open-Source LLMs: Your Fine-tuning Data Could Be Secretly Stolen!

21 May 2025

Papers citing "Be Careful When Fine-tuning On Open-Source LLMs: Your Fine-tuning Data Could Be Secretly Stolen!"

3 / 3 papers shown

Title
AISafetyLab: A Comprehensive Framework for AI Safety Evaluation and Improvement Zhexin Zhang Leqi Lei Junxiao Yang Xijie Huang Yida Lu ... Xianqi Lei Changzai Pan Lei Sha Han Wang Minlie Huang AAML 125 4 0 24 Feb 2025
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning DeepSeek-AI Daya Guo Dejian Yang Haowei Zhang Junxiao Song ... Shiyu Wang S. Yu Shunfeng Zhou Shuting Pan S.S. Li ReLM VLM OffRL AI4TS LRM 395 2,031 0 22 Jan 2025
Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators Yann Dubois Balázs Galambosi Percy Liang Tatsunori Hashimoto ALM 171 403 0 06 Apr 2024