ResearchTrend.AI
Federated Fine-Tuning of Large Language Models: Kahneman-Tversky vs. Direct Preference Optimization

Federated Fine-Tuning of Large Language Models: Kahneman-Tversky vs. Direct Preference Optimization

Fernando Spadea
Oshani Seneviratne
ArXivPDFHTML

Papers citing "Federated Fine-Tuning of Large Language Models: Kahneman-Tversky vs. Direct Preference Optimization"

3 / 3 papers shown
Title
Universal and Transferable Adversarial Attacks on Aligned Language Models
Universal and Transferable Adversarial Attacks on Aligned Language Models
Andy Zou
Zifan Wang
Nicholas Carlini
Milad Nasr
J. Zico Kolter
Matt Fredrikson
139
1,376
0
27 Jul 2023
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
Lianmin Zheng
Wei-Lin Chiang
Ying Sheng
Siyuan Zhuang
Zhanghao Wu
...
Dacheng Li
Eric Xing
Haotong Zhang
Joseph E. Gonzalez
Ion Stoica
ALM
OSLM
ELM
173
4,085
0
09 Jun 2023
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
T. Hsu
Qi
Matthew Brown
FedML
99
1,128
0
13 Sep 2019

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.