ICML "direct preference optimization" Papers
10 papers found
Active Preference Learning for Large Language Models
William Muldrew, Peter Hayes, Mingtian Zhang et al.
ICML 2024poster
A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity
Andrew Lee, Xiaoyan Bai, Itamar Pres et al.
ICML 2024poster
BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback
Gaurav Pandey, Yatin Nandwani, Tahira Naseem et al.
ICML 2024poster
GRATH: Gradual Self-Truthifying for Large Language Models
Weixin Chen, Dawn Song, Bo Li
ICML 2024poster
Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study
Shusheng Xu, Wei Fu, Jiaxuan Gao et al.
ICML 2024poster
Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint
Wei Xiong, Hanze Dong, Chenlu Ye et al.
ICML 2024poster
Provably Robust DPO: Aligning Language Models with Noisy Feedback
Sayak Ray Chowdhury, Anush Kini, Nagarajan Natarajan
ICML 2024poster
Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences
Andi Nika, Debmalya Mandal, Parameswaran Kamalaruban et al.
ICML 2024poster
Token-level Direct Preference Optimization
Yongcheng Zeng, Guoqing Liu, Weiyu Ma et al.
ICML 2024poster
Towards Efficient Exact Optimization of Language Model Alignment
Haozhe Ji, Cheng Lu, Yilin Niu et al.
ICML 2024poster