Cover Image

Generative Reward Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mahan, Dakota, Van Phung, Duy, Rafailov, Rafael, Blagden, Chase, Lile, Nathan, Castricato, Louis, Fränken, Jan-Philipp, Finn, Chelsea, Albalak, Alon
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models
by: Albalak, Alon, et al.
Published: (2025)

Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought
by: Xiang, Violet, et al.
Published: (2025)

PERSONA: A Reproducible Testbed for Pluralistic Alignment
by: Castricato, Louis, et al.
Published: (2024)

Just Enough Thinking: Efficient Reasoning with Adaptive Length Penalties Reinforcement Learning
by: Xiang, Violet, et al.
Published: (2025)

From $r$ to $Q^*$: Your Language Model is Secretly a Q-Function
by: Rafailov, Rafael, et al.
Published: (2024)

Direct Preference Optimization: Your Language Model is Secretly a Reward Model
by: Rafailov, Rafael, et al.
Published: (2023)

Efficient Imitation Learning with Conservative World Models
by: Kolev, Victor, et al.
Published: (2024)

Disentangling Length from Quality in Direct Preference Optimization
by: Park, Ryan, et al.
Published: (2024)

Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms
by: Rafailov, Rafael, et al.
Published: (2024)

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models
by: Havrilla, Alex, et al.
Published: (2024)

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning
by: Zhou, Yiyang, et al.
Published: (2024)

MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning
by: Rafailov, Rafael, et al.
Published: (2024)

Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents
by: Putta, Pranav, et al.
Published: (2024)

Contrastive Preference Learning: Learning from Human Feedback without RL
by: Hejna, Joey, et al.
Published: (2023)

Scalable Ensembling For Mitigating Reward Overoptimisation
by: Ahmed, Ahmed M., et al.
Published: (2024)

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data
by: Tajwar, Fahim, et al.
Published: (2024)

Self-Directed Synthetic Dialogues and Revisions Technical Report
by: Lambert, Nathan, et al.
Published: (2024)

Improved Bounds for Reward-Agnostic and Reward-Free Exploration
by: Ridel, Oran, et al.
Published: (2026)

Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data
by: Wang, Xinyi, et al.
Published: (2024)

MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?
by: Chen, Zhaorun, et al.
Published: (2024)

Feedback Descent: Open-Ended Text Optimization via Pairwise Comparison
by: Lee, Yoonho, et al.
Published: (2025)

D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning
by: Rafailov, Rafael, et al.
Published: (2024)

Universal Neural Functionals
by: Zhou, Allan, et al.
Published: (2024)

Stable LM 2 1.6B Technical Report
by: Bellagente, Marco, et al.
Published: (2024)

A Mathematical Framework and a Suite of Learning Techniques for Neural-Symbolic Systems
by: Dickens, Charles, et al.
Published: (2024)

Improving Domain Generalization with Domain Relations
by: Yao, Huaxiu, et al.
Published: (2023)

Efficient Data Collection for Robotic Manipulation via Compositional Generalization
by: Gao, Jensen, et al.
Published: (2024)

Suppressing Pink Elephants with Direct Principle Feedback
by: Castricato, Louis, et al.
Published: (2024)

Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
by: Kim, Moo Jin, et al.
Published: (2025)

RewardBench: Evaluating Reward Models for Language Modeling
by: Lambert, Nathan, et al.
Published: (2024)

Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval
by: Hsu, Sheryl, et al.
Published: (2024)

Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning
by: Xie, Johnathan, et al.
Published: (2024)

EXPO: Stable Reinforcement Learning with Expressive Policies
by: Dong, Perry, et al.
Published: (2025)

FASTER: Value-Guided Sampling for Fast RL
by: Dong, Perry, et al.
Published: (2026)

OpenVLA: An Open-Source Vision-Language-Action Model
by: Kim, Moo Jin, et al.
Published: (2024)

A Survey on Data Selection for Language Models
by: Albalak, Alon, et al.
Published: (2024)

Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs
by: Gandhi, Kanishk, et al.
Published: (2025)

LASeR: Learning to Adaptively Select Reward Models with Multi-Armed Bandits
by: Nguyen, Duy, et al.
Published: (2024)

Collapse or Thrive? Perils and Promises of Synthetic Data in a Self-Generating World
by: Kazdan, Joshua, et al.
Published: (2024)

Calibrating Language Models with Adaptive Temperature Scaling
by: Xie, Johnathan, et al.
Published: (2024)