Cover Image

Label-Free Reinforcement Learning via Cross-Model Entropy

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gorbett, Matt, Shirazi, Hossein
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tiled Bit Networks: Sub-Bit Neural Network Compression Through Reuse of Learnable Binary Vectors
by: Gorbett, Matt, et al.
Published: (2024)

Cross-Model Disagreement as a Label-Free Correctness Signal
by: Gorbett, Matt, et al.
Published: (2026)

Cross-Silo Federated Learning Across Divergent Domains with Iterative Parameter Alignment
by: Gorbett, Matt, et al.
Published: (2023)

DISCO-TAB: A Hierarchical Reinforcement Learning Framework for Privacy-Preserving Synthesis of Complex Clinical Data
by: Ilaty, Arshia, et al.
Published: (2026)

You Need Reasoning to Learn Reasoning: The Limitations of Label-Free RL in Weak Base Models
by: Roy, Shuvendu, et al.
Published: (2025)

Characterizing Linear Alignment Across Language Models
by: Gorbett, Matt, et al.
Published: (2026)

Addressing Label Shift in Distributed Learning via Entropy Regularization
by: Wu, Zhiyuan, et al.
Published: (2025)

Entropy-Preserving Reinforcement Learning
by: Petrenko, Aleksei, et al.
Published: (2026)

Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
by: Yoon, Sangwoong, et al.
Published: (2024)

Entropy-Aware Model Initialization for Effective Exploration in Deep Reinforcement Learning
by: Jang, Sooyoung, et al.
Published: (2021)

Boosting Maximum Entropy Reinforcement Learning via One-Step Flow Matching
by: Li, Zeqiao, et al.
Published: (2026)

Learning to Clean: Reinforcement Learning for Noisy Label Correction
by: Heidari, Marzi, et al.
Published: (2025)

Maximum Entropy Reinforcement Learning with Diffusion Policy
by: Dong, Xiaoyi, et al.
Published: (2025)

Interpreting Emergent Planning in Model-Free Reinforcement Learning
by: Bush, Thomas, et al.
Published: (2025)

Towards General-Purpose Model-Free Reinforcement Learning
by: Fujimoto, Scott, et al.
Published: (2025)

Smoothie: Label Free Language Model Routing
by: Guha, Neel, et al.
Published: (2024)

Entropy-Regularized Adjoint Matching for Offline Reinforcement Learning
by: Ghanem, Abdelghani, et al.
Published: (2026)

Model-Free Robust Reinforcement Learning with Sample Complexity Analysis
by: Wang, Yudan, et al.
Published: (2024)

The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models
by: Cui, Ganqu, et al.
Published: (2025)

Revisiting Entropy in Reinforcement Learning for Large Reasoning Models
by: Jin, Renren, et al.
Published: (2025)

Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration
by: Kim, Dongyoung, et al.
Published: (2023)

Reward-Punishment Reinforcement Learning with Maximum Entropy
by: Wang, Jiexin, et al.
Published: (2024)

A Reinforcement Learning-Based Task Mapping Method to Improve the Reliability of Clustered Manycores
by: Hossein-Khani, Fatemeh, et al.
Published: (2024)

LICORICE: Label-Efficient Concept-Based Interpretable Reinforcement Learning
by: Ye, Zhuorui, et al.
Published: (2024)

SymCircuit: Bayesian Structure Inference for Tractable Probabilistic Circuits via Entropy-Regularized Reinforcement Learning
by: Ju, Y. Sungtaek
Published: (2026)

Learning Rewards, Not Labels: Adversarial Inverse Reinforcement Learning for Machinery Fault Detection
by: Neupane, Dhiraj, et al.
Published: (2026)

ORAN-GUIDE: RAG-Driven Prompt Learning for LLM-Augmented Reinforcement Learning in O-RAN Network Slicing
by: Lotfi, Fatemeh, et al.
Published: (2025)

On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
by: Wang, Shumin, et al.
Published: (2026)

A Comprehensive Survey of Reinforcement Learning: From Algorithms to Practical Challenges
by: Ghasemi, Majid, et al.
Published: (2024)

Efficient Triple Modular Redundancy for Reliability Enhancement of DNNs Using Explainable AI
by: Soroush, Kimia, et al.
Published: (2025)

Towards Interpretable Deep Reinforcement Learning Models via Inverse Reinforcement Learning
by: Xie, Sean, et al.
Published: (2022)

Reinforcing privacy reasoning in LLMs via normative simulacra from fiction
by: Franchi, Matt, et al.
Published: (2026)

ECHO: Entropy-Confidence Hybrid Optimization for Test-Time Reinforcement Learning
by: Zhao, Chu, et al.
Published: (2026)

Diffusion-Augmented Markov Decision Processes for Maximum Entropy Reinforcement Learning
by: Sanokowski, Sebastian, et al.
Published: (2025)

Constrained Reinforcement Learning with Average Reward Objective: Model-Based and Model-Free Algorithms
by: Aggarwal, Vaneet, et al.
Published: (2024)

Semantically Labelled Automata for Multi-Task Reinforcement Learning with LTL Instructions
by: Abate, Alessandro, et al.
Published: (2026)

Regret-Free Reinforcement Learning for LTL Specifications
by: Majumdar, Rupak, et al.
Published: (2024)

NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning
by: Liu, Wei, et al.
Published: (2025)

Source-Free Cross-Domain Continual Learning
by: Furqon, Muhammad Tanzil, et al.
Published: (2025)

Training-Free Geospatial Place Representation Learning from Large-Scale Point-of-Interest Graph Data
by: Hashemi, Mohammad, et al.
Published: (2025)