Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2505.15656
Cited By
Be Careful When Fine-tuning On Open-Source LLMs: Your Fine-tuning Data Could Be Secretly Stolen!
21 May 2025
Zhexin Zhang
Yuhao Sun
Junxiao Yang
Shiyao Cui
Hongning Wang
Shiyu Huang
AAML
Re-assign community
ArXiv (abs)
PDF
HTML
HuggingFace (14 upvotes)
Papers citing
"Be Careful When Fine-tuning On Open-Source LLMs: Your Fine-tuning Data Could Be Secretly Stolen!"
4 / 4 papers shown
Offline and Online KL-Regularized RLHF under Differential Privacy
Yulian Wu
Rushil Thareja
Praneeth Vepakomma
Francesco Orabona
OffRL
117
0
0
15 Oct 2025
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
Shiyu Huang
AAML
247
10
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
OffRL
AI4TS
LRM
ReLM
VLM
1.2K
5,342
0
22 Jan 2025
Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators
Yann Dubois
Balázs Galambosi
Abigail Z. Jacobs
Tatsunori Hashimoto
ALM
455
601
0
06 Apr 2024
1
