Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge
Fuente:
arXiv
Saved in:
| Main Authors: | Wu, Tianhao, Yuan, Weizhe, Golovneva, Olga, Xu, Jing, Tian, Yuandong, Jiao, Jiantao, Weston, Jason, Sukhbaatar, Sainbayar |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
R.I.P.: Better Models by Survival of the Fittest Prompts
by: Yu, Ping, et al.
Published: (2025)
by: Yu, Ping, et al.
Published: (2025)
Thinking LLMs: General Instruction Following with Thought Generation
by: Wu, Tianhao, et al.
Published: (2024)
by: Wu, Tianhao, et al.
Published: (2024)
StepWiser: Stepwise Generative Judges for Wiser Reasoning
by: Xiong, Wei, et al.
Published: (2025)
by: Xiong, Wei, et al.
Published: (2025)
Multi-Token Attention
by: Golovneva, Olga, et al.
Published: (2025)
by: Golovneva, Olga, et al.
Published: (2025)
Contextual Position Encoding: Learning to Count What's Important
by: Golovneva, Olga, et al.
Published: (2024)
by: Golovneva, Olga, et al.
Published: (2024)
Self-Rewarding Language Models
by: Yuan, Weizhe, et al.
Published: (2024)
by: Yuan, Weizhe, et al.
Published: (2024)
Reverse Training to Nurse the Reversal Curse
by: Golovneva, Olga, et al.
Published: (2024)
by: Golovneva, Olga, et al.
Published: (2024)
CoT-Self-Instruct: Building high-quality synthetic prompts for reasoning and non-reasoning tasks
by: Yu, Ping, et al.
Published: (2025)
by: Yu, Ping, et al.
Published: (2025)
Some things are more CRINGE than others: Iterative Preference Optimization with the Pairwise Cringe Loss
by: Xu, Jing, et al.
Published: (2023)
by: Xu, Jing, et al.
Published: (2023)
Following Length Constraints in Instructions
by: Yuan, Weizhe, et al.
Published: (2024)
by: Yuan, Weizhe, et al.
Published: (2024)
Self-Challenging Language Model Agents
by: Zhou, Yifei, et al.
Published: (2025)
by: Zhou, Yifei, et al.
Published: (2025)
Training Large Language Models to Reason in a Continuous Latent Space
by: Hao, Shibo, et al.
Published: (2024)
by: Hao, Shibo, et al.
Published: (2024)
Iterative Reasoning Preference Optimization
by: Pang, Richard Yuanzhe, et al.
Published: (2024)
by: Pang, Richard Yuanzhe, et al.
Published: (2024)
SPICE: Self-Play In Corpus Environments Improves Reasoning
by: Liu, Bo, et al.
Published: (2025)
by: Liu, Bo, et al.
Published: (2025)
Self-Improving Pretraining: using post-trained models to pretrain better models
by: Tan, Ellen Xiaoqing, et al.
Published: (2026)
by: Tan, Ellen Xiaoqing, et al.
Published: (2026)
Self-Consistency Preference Optimization
by: Prasad, Archiki, et al.
Published: (2024)
by: Prasad, Archiki, et al.
Published: (2024)
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
by: Sukhbaatar, Sainbayar, et al.
Published: (2024)
by: Sukhbaatar, Sainbayar, et al.
Published: (2024)
SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks
by: Zhou, Yifei, et al.
Published: (2025)
by: Zhou, Yifei, et al.
Published: (2025)
System-Level Natural Language Feedback
by: Yuan, Weizhe, et al.
Published: (2023)
by: Yuan, Weizhe, et al.
Published: (2023)
Adaptive Decoding via Latent Preference Optimization
by: Dhuliawala, Shehzaad, et al.
Published: (2024)
by: Dhuliawala, Shehzaad, et al.
Published: (2024)
Diverse Preference Optimization
by: Lanchantin, Jack, et al.
Published: (2025)
by: Lanchantin, Jack, et al.
Published: (2025)
Bridging Offline and Online Reinforcement Learning for LLMs
by: Lanchantin, Jack, et al.
Published: (2025)
by: Lanchantin, Jack, et al.
Published: (2025)
Self-Taught Evaluators
by: Wang, Tianlu, et al.
Published: (2024)
by: Wang, Tianlu, et al.
Published: (2024)
Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning
by: Su, DiJia, et al.
Published: (2025)
by: Su, DiJia, et al.
Published: (2025)
EmbedLLM: Learning Compact Representations of Large Language Models
by: Zhuang, Richard, et al.
Published: (2024)
by: Zhuang, Richard, et al.
Published: (2024)
MM-Eval: A Multilingual Meta-Evaluation Benchmark for LLM-as-a-Judge and Reward Models
by: Son, Guijin, et al.
Published: (2024)
by: Son, Guijin, et al.
Published: (2024)
One Adapts to Any: Meta Reward Modeling for Personalized LLM Alignment
by: Cai, Hongru, et al.
Published: (2026)
by: Cai, Hongru, et al.
Published: (2026)
The Era of Real-World Human Interaction: RL from User Conversations
by: Jin, Chuanyang, et al.
Published: (2025)
by: Jin, Chuanyang, et al.
Published: (2025)
Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces
by: Su, DiJia, et al.
Published: (2024)
by: Su, DiJia, et al.
Published: (2024)
R-Align: Enhancing Generative Reward Models through Rationale-Centric Meta-Judging
by: Lai, Yanlin, et al.
Published: (2026)
by: Lai, Yanlin, et al.
Published: (2026)
Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge
by: Saha, Swarnadeep, et al.
Published: (2025)
by: Saha, Swarnadeep, et al.
Published: (2025)
SEAL: Can Saturated Benchmarks Be Revived by LLM-as-a-Meta-Judge?
by: Chen, Jiamin, et al.
Published: (2026)
by: Chen, Jiamin, et al.
Published: (2026)
RESTRAIN: From Spurious Votes to Signals -- Self-Driven RL with Self-Penalization
by: Yu, Zhaoning, et al.
Published: (2025)
by: Yu, Zhaoning, et al.
Published: (2025)
NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions
by: Yuan, Weizhe, et al.
Published: (2025)
by: Yuan, Weizhe, et al.
Published: (2025)
PocketLLM: Ultimate Compression of Large Language Models via Meta Networks
by: Tian, Ye, et al.
Published: (2025)
by: Tian, Ye, et al.
Published: (2025)
Self-Alignment with Instruction Backtranslation
by: Li, Xian, et al.
Published: (2023)
by: Li, Xian, et al.
Published: (2023)
LLM Pretraining with Continuous Concepts
by: Tack, Jihoon, et al.
Published: (2025)
by: Tack, Jihoon, et al.
Published: (2025)
LLM as a Meta-Judge: Synthetic Data for NLP Evaluation Metric Validation
by: Eigler, Lukáš, et al.
Published: (2026)
by: Eigler, Lukáš, et al.
Published: (2026)
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics
by: Zhu, Hanlin, et al.
Published: (2024)
by: Zhu, Hanlin, et al.
Published: (2024)
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
by: Zhu, Banghua, et al.
Published: (2024)
by: Zhu, Banghua, et al.
Published: (2024)
Similar Items
-
R.I.P.: Better Models by Survival of the Fittest Prompts
by: Yu, Ping, et al.
Published: (2025) -
Thinking LLMs: General Instruction Following with Thought Generation
by: Wu, Tianhao, et al.
Published: (2024) -
StepWiser: Stepwise Generative Judges for Wiser Reasoning
by: Xiong, Wei, et al.
Published: (2025) -
Multi-Token Attention
by: Golovneva, Olga, et al.
Published: (2025) -
Contextual Position Encoding: Learning to Count What's Important
by: Golovneva, Olga, et al.
Published: (2024)