Diffusion World Model
Paper • 2402.03570 • Published • 8
RL
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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 • 1 -
ODIN: Disentangled Reward Mitigates Hacking in RLHF
Paper • 2402.07319 • Published • 14 -
Preference-free Alignment Learning with Regularized Relevance Reward
Paper • 2402.03469 • Published -
Teaching Large Language Models to Reason with Reinforcement Learning
Paper • 2403.04642 • Published • 48 -
RewardBench: Evaluating Reward Models for Language Modeling
Paper • 2403.13787 • Published • 22 -
PERL: Parameter Efficient Reinforcement Learning from Human Feedback
Paper • 2403.10704 • Published • 60 -
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
Paper • 2403.03950 • Published • 15 -
In deep reinforcement learning, a pruned network is a good network
Paper • 2402.12479 • Published • 19 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 62 -
Learn Your Reference Model for Real Good Alignment
Paper • 2404.09656 • Published • 90 -
Offline Regularised Reinforcement Learning for Large Language Models Alignment
Paper • 2405.19107 • Published • 15 -
Self-Improving Robust Preference Optimization
Paper • 2406.01660 • Published • 20 -
Mistral-C2F: Coarse to Fine Actor for Analytical and Reasoning Enhancement in RLHF and Effective-Merged LLMs
Paper • 2406.08657 • Published • 10 -
BPO: Supercharging Online Preference Learning by Adhering to the Proximity of Behavior LLM
Paper • 2406.12168 • Published • 7 -
THEANINE: Revisiting Memory Management in Long-term Conversations with Timeline-augmented Response Generation
Paper • 2406.10996 • Published • 35 -
WPO: Enhancing RLHF with Weighted Preference Optimization
Paper • 2406.11827 • Published • 17 -
Understanding and Diagnosing Deep Reinforcement Learning
Paper • 2406.16979 • Published • 10 -
Gradient Boosting Reinforcement Learning
Paper • 2407.08250 • Published • 13 -
Understanding Reference Policies in Direct Preference Optimization
Paper • 2407.13709 • Published • 17 -
Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration
Paper • 2410.18076 • Published • 4 -
Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS
Paper • 2411.18478 • Published • 37 -
A Simple and Provable Scaling Law for the Test-Time Compute of Large Language Models
Paper • 2411.19477 • Published • 6 -
A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce
Paper • 2504.11343 • Published • 20