conftrace_

reward model

276 papers

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Also known as

RM

Co-occurring keywords

large language model (13587) reinforcement learning (4352) reinforcement learning from human feedback (278) language model (4599) preference learning (418) language model alignment (142) reward modeling (164) direct preference optimization (332) human feedback (161) human preference (124)

Papers

Aligning to Thousands of Preferences via System Message Generalization NIPS 2024
ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search NIPS 2024
Geometric-Averaged Preference Optimization for Soft Preference Labels NIPS 2024
Rich Human Feedback for Text-to-Image Generation CVPR 2024
Filtered Direct Preference Optimization EMNLP 2024
Fast Best-of-N Decoding via Speculative Rejection NIPS 2024
Reinforcement Learning from Answer Reranking Feedback for Retrieval-Augmented Answer Generation INTERSPEECH 2024
A Reinforcement Learning Approach to Improve Low-Resource Machine Translation Leveraging Domain Monolingual Data COLING 2024
UltraMedical: Building Specialized Generalists in Biomedicine NIPS 2024
Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation EMNLP 2024
LINKED: Eliciting, Filtering and Integrating Knowledge in Large Language Model for Commonsense Reasoning EMNLP 2024
TS-Align: A Teacher-Student Collaborative Framework for Scalable Iterative Finetuning of Large Language Models EMNLP 2024
On Diversified Preferences of Large Language Model Alignment EMNLP 2024
Margin Matching Preference Optimization: Enhanced Model Alignment with Granular Feedback EMNLP 2024
Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences NIPS 2024
Rule Based Rewards for Language Model Safety NIPS 2024
Noise Contrastive Alignment of Language Models with Explicit Rewards NIPS 2024
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms NIPS 2024
Boosting Text-to-Video Generative Model with MLLMs Feedback NIPS 2024
Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models NIPS 2024
Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment NIPS 2024
Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback NIPS 2024
Improving Discriminative Capability of Reward Models in RLHF Using Contrastive Learning EMNLP 2024
EPO: Hierarchical LLM Agents with Environment Preference Optimization EMNLP 2024
GDPO: Learning to Directly Align Language Models with Diversity Using GFlowNets EMNLP 2024