-
RLHF Workflow: From Reward Modeling to Online RLHF
Paper • 2405.07863 • Published • 67 -
Understanding and Diagnosing Deep Reinforcement Learning
Paper • 2406.16979 • Published • 9 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 60 -
Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning
Paper • 2407.00617 • Published • 7
Collections
Discover the best community collections!
Collections including paper arxiv:2406.11827
-
Bootstrapping Language Models with DPO Implicit Rewards
Paper • 2406.09760 • Published • 38 -
BPO: Supercharging Online Preference Learning by Adhering to the Proximity of Behavior LLM
Paper • 2406.12168 • Published • 7 -
WPO: Enhancing RLHF with Weighted Preference Optimization
Paper • 2406.11827 • Published • 14 -
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Paper • 2406.18629 • Published • 40
-
mDPO: Conditional Preference Optimization for Multimodal Large Language Models
Paper • 2406.11839 • Published • 37 -
Pandora: Towards General World Model with Natural Language Actions and Video States
Paper • 2406.09455 • Published • 14 -
WPO: Enhancing RLHF with Weighted Preference Optimization
Paper • 2406.11827 • Published • 14 -
In-Context Editing: Learning Knowledge from Self-Induced Distributions
Paper • 2406.11194 • Published • 15
-
WPO: Enhancing RLHF with Weighted Preference Optimization
Paper • 2406.11827 • Published • 14 -
Self-Improving Robust Preference Optimization
Paper • 2406.01660 • Published • 18 -
Bootstrapping Language Models with DPO Implicit Rewards
Paper • 2406.09760 • Published • 38 -
BPO: Supercharging Online Preference Learning by Adhering to the Proximity of Behavior LLM
Paper • 2406.12168 • Published • 7
-
Diffusion World Model
Paper • 2402.03570 • Published • 7 -
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
Paper • 2401.16335 • Published • 1 -
Towards Efficient and Exact Optimization of Language Model Alignment
Paper • 2402.00856 • Published -
ODIN: Disentangled Reward Mitigates Hacking in RLHF
Paper • 2402.07319 • Published • 13
-
Moral Foundations of Large Language Models
Paper • 2310.15337 • Published • 1 -
Specific versus General Principles for Constitutional AI
Paper • 2310.13798 • Published • 2 -
Contrastive Prefence Learning: Learning from Human Feedback without RL
Paper • 2310.13639 • Published • 24 -
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Paper • 2309.00267 • Published • 47