Expanding the Capabilities of Reinforcement Learning via Text Feedback
Fuente:
arXiv
Saved in:
| Main Authors: | Song, Yuda, Chen, Lili, Tajwar, Fahim, Munos, Remi, Pathak, Deepak, Bagnell, J. Andrew, Singh, Aarti, Zanette, Andrea |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Hybrid Reinforcement Learning from Offline Observation Alone
by: Song, Yuda, et al.
Published: (2024)
by: Song, Yuda, et al.
Published: (2024)
To Distill or Decide? Understanding the Algorithmic Trade-off in Partially Observable Reinforcement Learning
by: Song, Yuda, et al.
Published: (2025)
by: Song, Yuda, et al.
Published: (2025)
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage
by: Song, Yuda, et al.
Published: (2024)
by: Song, Yuda, et al.
Published: (2024)
Accelerating Unbiased LLM Evaluation via Synthetic Feedback
by: Zhou, Zhaoyi, et al.
Published: (2025)
by: Zhou, Zhaoyi, et al.
Published: (2025)
Maximum Likelihood Reinforcement Learning
by: Tajwar, Fahim, et al.
Published: (2026)
by: Tajwar, Fahim, et al.
Published: (2026)
Outcome-based Exploration for LLM Reasoning
by: Song, Yuda, et al.
Published: (2025)
by: Song, Yuda, et al.
Published: (2025)
Can Large Reasoning Models Self-Train?
by: Shafayat, Sheikh, et al.
Published: (2025)
by: Shafayat, Sheikh, et al.
Published: (2025)
Inverse Reinforcement Learning without Reinforcement Learning
by: Swamy, Gokul, et al.
Published: (2023)
by: Swamy, Gokul, et al.
Published: (2023)
Rich-Observation Reinforcement Learning with Continuous Latent Dynamics
by: Song, Yuda, et al.
Published: (2024)
by: Song, Yuda, et al.
Published: (2024)
Optimizing Language Models for Inference Time Objectives using Reinforcement Learning
by: Tang, Yunhao, et al.
Published: (2025)
by: Tang, Yunhao, et al.
Published: (2025)
Beyond Verifiable Rewards: Scaling Reinforcement Learning for Language Models to Unverifiable Data
by: Tang, Yunhao, et al.
Published: (2025)
by: Tang, Yunhao, et al.
Published: (2025)
On a few pitfalls in KL divergence gradient estimation for RL
by: Tang, Yunhao, et al.
Published: (2025)
by: Tang, Yunhao, et al.
Published: (2025)
Splats under Pressure: Exploring Performance-Energy Trade-offs in Real-Time 3D Gaussian Splatting under Constrained GPU Budgets
by: Tajwar, Muhammad Fahim, et al.
Published: (2026)
by: Tajwar, Muhammad Fahim, et al.
Published: (2026)
The Virtues of Pessimism in Inverse Reinforcement Learning
by: Wu, David, et al.
Published: (2024)
by: Wu, David, et al.
Published: (2024)
Super-Exponential Regret for UCT, AlphaGo and Variants
by: Orseau, Laurent, et al.
Published: (2024)
by: Orseau, Laurent, et al.
Published: (2024)
Hybrid Inverse Reinforcement Learning
by: Ren, Juntao, et al.
Published: (2024)
by: Ren, Juntao, et al.
Published: (2024)
SPEED-RL: Faster Training of Reasoning Models via Online Curriculum Learning
by: Zhang, Ruiqi, et al.
Published: (2025)
by: Zhang, Ruiqi, et al.
Published: (2025)
All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning
by: Swamy, Gokul, et al.
Published: (2025)
by: Swamy, Gokul, et al.
Published: (2025)
Multi-turn Reinforcement Learning from Preference Human Feedback
by: Shani, Lior, et al.
Published: (2024)
by: Shani, Lior, et al.
Published: (2024)
Reasoning as an Adaptive Defense for Safety
by: Kim, Taeyoun, et al.
Published: (2025)
by: Kim, Taeyoun, et al.
Published: (2025)
Shrinking the Variance: Shrinkage Baselines for Reinforcement Learning with Verifiable Rewards
by: Zeng, Guanning, et al.
Published: (2025)
by: Zeng, Guanning, et al.
Published: (2025)
Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model
by: Rowland, Mark, et al.
Published: (2024)
by: Rowland, Mark, et al.
Published: (2024)
Bandits attack function optimization
by: Preux, Philippe, et al.
Published: (2026)
by: Preux, Philippe, et al.
Published: (2026)
Stochastic simultaneous optimistic optimization
by: Valko, Michal, et al.
Published: (2026)
by: Valko, Michal, et al.
Published: (2026)
Retrospective In-Context Learning for Temporal Credit Assignment with Large Language Models
by: Chen, Wen-Tse, et al.
Published: (2026)
by: Chen, Wen-Tse, et al.
Published: (2026)
Conservative Prediction via Data-Driven Confidence Minimization
by: Choi, Caroline, et al.
Published: (2023)
by: Choi, Caroline, et al.
Published: (2023)
Asymmetric REINFORCE for off-Policy Reinforcement Learning: Balancing positive and negative rewards
by: Arnal, Charles, et al.
Published: (2025)
by: Arnal, Charles, et al.
Published: (2025)
Black-box optimization of noisy functions with unknown smoothness
by: Grill, Jean-Bastien, et al.
Published: (2026)
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)
by: Grill, Jean-Bastien, et al.
Published: (2026)
State Combinatorial Generalization In Decision Making With Conditional Diffusion Models
by: Duan, Xintong, et al.
Published: (2025)
by: Duan, Xintong, et al.
Published: (2025)
Accelerating Diffusion Planners in Offline RL via Reward-Aware Consistency Trajectory Distillation
by: Duan, Xintong, et al.
Published: (2025)
by: Duan, Xintong, et al.
Published: (2025)
Spectral Thompson sampling
by: Kocak, Tomas, et al.
Published: (2026)
by: Kocak, Tomas, et al.
Published: (2026)
VA-learning as a more efficient alternative to Q-learning
by: Tang, Yunhao, et al.
Published: (2023)
by: Tang, Yunhao, et al.
Published: (2023)
Spectral bandits for smooth graph functions
by: Valko, Michal, et al.
Published: (2026)
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)
by: Kocak, Tomas, et al.
Published: (2026)
Training Language Models to Reason Efficiently
by: Arora, Daman, et al.
Published: (2025)
by: Arora, Daman, et al.
Published: (2025)
Is Offline Decision Making Possible with Only Few Samples? Reliable Decisions in Data-Starved Bandits via Trust Region Enhancement
by: Zhang, Ruiqi, et al.
Published: (2024)
by: Zhang, Ruiqi, et al.
Published: (2024)
Self-Questioning Language Models
by: Chen, Lili, et al.
Published: (2025)
by: Chen, Lili, et al.
Published: (2025)
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data
by: Tajwar, Fahim, et al.
Published: (2024)
by: Tajwar, Fahim, et al.
Published: (2024)
Spectral bandits for smooth graph functions with applications in recommender systems
by: Kocák, Tomáš, et al.
Published: (2026)
by: Kocák, Tomáš, et al.
Published: (2026)
Similar Items
-
Hybrid Reinforcement Learning from Offline Observation Alone
by: Song, Yuda, et al.
Published: (2024) -
To Distill or Decide? Understanding the Algorithmic Trade-off in Partially Observable Reinforcement Learning
by: Song, Yuda, et al.
Published: (2025) -
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage
by: Song, Yuda, et al.
Published: (2024) -
Accelerating Unbiased LLM Evaluation via Synthetic Feedback
by: Zhou, Zhaoyi, et al.
Published: (2025) -
Maximum Likelihood Reinforcement Learning
by: Tajwar, Fahim, et al.
Published: (2026)