Cover Image

Nash Learning from Human Feedback

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Munos, Rémi, Valko, Michal, Calandriello, Daniele, Azar, Mohammad Gheshlaghi, Rowland, Mark, Guo, Zhaohan Daniel, Tang, Yunhao, Geist, Matthieu, Mesnard, Thomas, Michi, Andrea, Selvi, Marco, Girgin, Sertan, Momchev, Nikola, Bachem, Olivier, Mankowitz, Daniel J., Precup, Doina, Piot, Bilal
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence Computer Science and Game Theory Multiagent Systems
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generalized Preference Optimization: A Unified Approach to Offline Alignment
by: Tang, Yunhao, et al.
Published: (2024)

VA-learning as a more efficient alternative to Q-learning
by: Tang, Yunhao, et al.
Published: (2023)

Human Alignment of Large Language Models through Online Preference Optimisation
by: Calandriello, Daniele, et al.
Published: (2024)

An Analysis of Quantile Temporal-Difference Learning
by: Rowland, Mark, et al.
Published: (2023)

Understanding the performance gap between online and offline alignment algorithms
by: Tang, Yunhao, et al.
Published: (2024)

On a few pitfalls in KL divergence gradient estimation for RL
by: Tang, Yunhao, et al.
Published: (2025)

Offline Regularised Reinforcement Learning for Large Language Models Alignment
by: Richemond, Pierre Harvey, et al.
Published: (2024)

Bandits attack function optimization
by: Preux, Philippe, et al.
Published: (2026)

Stochastic simultaneous optimistic optimization
by: Valko, Michal, et al.
Published: (2026)

RL-finetuning LLMs from on- and off-policy data with a single algorithm
by: Tang, Yunhao, et al.
Published: (2025)

Off-policy Distributional Q($λ$): Distributional RL without Importance Sampling
by: Tang, Yunhao, et al.
Published: (2024)

Black-box optimization of noisy functions with unknown smoothness
by: Grill, Jean-Bastien, et al.
Published: (2026)

Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning
by: Grill, Jean-Bastien, et al.
Published: (2026)

Self-Improving Robust Preference Optimization
by: Choi, Eugene, et al.
Published: (2024)

Spectral Thompson sampling
by: Kocak, Tomas, et al.
Published: (2026)

Spectral bandits for smooth graph functions
by: Valko, Michal, et al.
Published: (2026)

Efficient learning by implicit exploration in bandit problems with side observations
by: Kocak, Tomas, et al.
Published: (2026)

Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model
by: Rowland, Mark, et al.
Published: (2024)

Model-free Posterior Sampling via Learning Rate Randomization
by: Tiapkin, Daniil, et al.
Published: (2023)

Diversity-Rewarded CFG Distillation
by: Cideron, Geoffrey, et al.
Published: (2024)

BOND: Aligning LLMs with Best-of-N Distillation
by: Sessa, Pier Giuseppe, et al.
Published: (2024)

Large-scale semi-supervised learning with online spectral graph sparsification
by: Calandriello, Daniele, et al.
Published: (2026)

Analysis of Nystrom method with sequential ridge leverage scores
by: Calandriello, Daniele, et al.
Published: (2026)

Pack only the essentials: Adaptive dictionary learning for kernel ridge regression
by: Calandriello, Daniele, et al.
Published: (2026)

Diversity-Enriched Option-Critic
by: Kamat, Anand, et al.
Published: (2020)

Functional Acceleration for Policy Mirror Descent
by: Chelu, Veronica, et al.
Published: (2024)

A Look at Value-Based Decision-Time vs. Background Planning Methods Across Different Settings
by: Alver, Safa, et al.
Published: (2022)

Proximal Point Nash Learning from Human Feedback
by: Tiapkin, Daniil, et al.
Published: (2025)

Optimizing Return Distributions with Distributional Dynamic Programming
by: Pires, Bernardo Ávila, et al.
Published: (2025)

Spectral bandits for smooth graph functions with applications in recommender systems
by: Kocák, Tomáš, et al.
Published: (2026)

Spectral bandits
by: Kocák, Tomáš, et al.
Published: (2026)

Beyond Verifiable Rewards: Scaling Reinforcement Learning for Language Models to Unverifiable Data
by: Tang, Yunhao, et al.
Published: (2025)

Optimizing Language Models for Inference Time Objectives using Reinforcement Learning
by: Tang, Yunhao, et al.
Published: (2025)

Learning in Mean Field Games: A Survey
by: Laurière, Mathieu, et al.
Published: (2022)

Multi-turn Reinforcement Learning from Preference Human Feedback
by: Shani, Lior, et al.
Published: (2024)

Improved large-scale graph learning through ridge spectral sparsification
by: Calandriello, Daniele, et al.
Published: (2026)

Planning in entropy-regularized Markov decision processes and games
by: Grill, Jean-Bastien, et al.
Published: (2026)

Balancing Plasticity and Stability with Fast and Slow Successor Features
by: Chua, Raymond, et al.
Published: (2026)

On the Privacy of Selection Mechanisms with Gaussian Noise
by: Lebensold, Jonathan, et al.
Published: (2024)

MusicRL: Aligning Music Generation to Human Preferences
by: Cideron, Geoffrey, et al.
Published: (2024)