Image de couverture de livre

D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Rafailov, Rafael, Hatch, Kyle, Singh, Anikait, Smith, Laura, Kumar, Aviral, Kostrikov, Ilya, Hansen-Estruch, Philippe, Kolev, Victor, Ball, Philip, Wu, Jiajun, Finn, Chelsea, Levine, Sergey
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Robotics
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Efficient Imitation Learning with Conservative World Models
par: Kolev, Victor, et autres
Publié: (2024)

Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning
par: Nakamoto, Mitsuhiko, et autres
Publié: (2023)

MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning
par: Rafailov, Rafael, et autres
Publié: (2024)

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data
par: Tajwar, Fahim, et autres
Publié: (2024)

Training Diffusion Models with Reinforcement Learning
par: Black, Kevin, et autres
Publié: (2023)

RLAD: Training LLMs to Discover Abstractions for Solving Reasoning Problems
par: Qu, Yuxiao, et autres
Publié: (2025)

Posterior Behavioral Cloning: Pretraining BC Policies for Efficient RL Finetuning
par: Wagenmaker, Andrew, et autres
Publié: (2025)

Is Value Learning Really the Main Bottleneck in Offline RL?
par: Park, Seohong, et autres
Publié: (2024)

Scaling Test-Time Compute Without Verification or RL is Suboptimal
par: Setlur, Amrith, et autres
Publié: (2025)

RACER: Epistemic Risk-Sensitive RL Enables Fast Driving with Fewer Crashes
par: Stachowicz, Kyle, et autres
Publié: (2024)

From $r$ to $Q^*$: Your Language Model is Secretly a Q-Function
par: Rafailov, Rafael, et autres
Publié: (2024)

Disentangling Length from Quality in Direct Preference Optimization
par: Park, Ryan, et autres
Publié: (2024)

DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning
par: Bai, Hao, et autres
Publié: (2024)

Contrastive Preference Learning: Learning from Human Feedback without RL
par: Hejna, Joey, et autres
Publié: (2023)

BridgeData V2: A Dataset for Robot Learning at Scale
par: Walke, Homer, et autres
Publié: (2023)

FSPO: Few-Shot Optimization of Synthetic Preferences Personalizes to Real Users
par: Singh, Anikait, et autres
Publié: (2025)

Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone
par: Mark, Max Sobol, et autres
Publié: (2024)

Video Occupancy Models
par: Tomar, Manan, et autres
Publié: (2024)

Vision-Language Models Provide Promptable Representations for Reinforcement Learning
par: Chen, William, et autres
Publié: (2024)

ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL
par: Zhou, Yifei, et autres
Publié: (2024)

Horizon Reduction Makes RL Scalable
par: Park, Seohong, et autres
Publié: (2025)

Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models
par: Albalak, Alon, et autres
Publié: (2025)

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning
par: Zhou, Yiyang, et autres
Publié: (2024)

Just Enough Thinking: Efficient Reasoning with Adaptive Length Penalties Reinforcement Learning
par: Xiang, Violet, et autres
Publié: (2025)

Test-Time Alignment via Hypothesis Reweighting
par: Lee, Yoonho, et autres
Publié: (2024)

Value-Based Deep RL Scales Predictably
par: Rybkin, Oleh, et autres
Publié: (2025)

Compute-Optimal Scaling for Value-Based Deep RL
par: Fu, Preston, et autres
Publié: (2025)

PERSONA: A Reproducible Testbed for Pluralistic Alignment
par: Castricato, Louis, et autres
Publié: (2024)

RLAC: Reinforcement Learning with Adversarial Critic for Free-Form Generation Tasks
par: Wu, Mian, et autres
Publié: (2025)

Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data
par: Zhou, Zhiyuan, et autres
Publié: (2024)

ViVa: Video-Trained Value Functions for Guiding Online RL from Diverse Data
par: Dashora, Nitish, et autres
Publié: (2025)

Adapt On-the-Go: Behavior Modulation for Single-Life Robot Deployment
par: Chen, Annie S., et autres
Publié: (2023)

Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
par: Hsu, Kyle, et autres
Publié: (2024)

FASTER: Value-Guided Sampling for Fast RL
par: Dong, Perry, et autres
Publié: (2026)

Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance
par: Nakamoto, Mitsuhiko, et autres
Publié: (2024)

Direct Preference Optimization: Your Language Model is Secretly a Reward Model
par: Rafailov, Rafael, et autres
Publié: (2023)

RoboReward: General-Purpose Vision-Language Reward Models for Robotics
par: Lee, Tony, et autres
Publié: (2026)

Robotic Control via Embodied Chain-of-Thought Reasoning
par: Zawalski, Michał, et autres
Publié: (2024)

Commonsense Reasoning for Legged Robot Adaptation with Vision-Language Models
par: Chen, Annie S., et autres
Publié: (2024)

Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought
par: Xiang, Violet, et autres
Publié: (2025)