Papers with Code 아카이브
Offline RL
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 2
- 보존된 평가 기록
- 4
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
From Novelty to Imitation: Self-Distilled Rewards for Offline Reinforcement Learning
Step-wise Policy for Rare-tool Knowledge (SPaRK): Offline RL that Drives Diverse Tool Use in LLMs
Robust Bandwidth Estimation for Real-Time Communication with Offline Reinforcement Learning
Optimal Single-Policy Sample Complexity and Transient Coverage for Average-Reward Offline RL
Flow-Based Single-Step Completion for Efficient and Expressive Policy Learning
Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity
CAWR: Corruption-Averse Advantage-Weighted Regression for Robust Policy Optimization
IntelliLung: Advancing Safe Mechanical Ventilation using Offline RL with Hybrid Actions and Clinically Aligned Rewards
Toward Explainable Offline RL: Analyzing Representations in Intrinsically Motivated Decision Transformers
DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty
MOORL: A Framework for Integrating Offline-Online Reinforcement Learning
Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood
MOBODY: Model Based Off-Dynamics Offline Reinforcement Learning
How to Provably Improve Return Conditioned Supervised Learning?
Semi-gradient DICE for Offline Constrained Reinforcement Learning
Policy-Based Trajectory Clustering in Offline Reinforcement Learning
Accelerating Diffusion Models in Offline RL via Reward-Aware Consistency Trajectory Distillation
Learning to Clarify by Reinforcement Learning Through Reward-Weighted Fine-Tuning
Enhanced DACER Algorithm with High Diffusion Efficiency
Diffusion Guidance Is a Controllable Policy Improvement Operator
ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning
Scaling Offline RL via Efficient and Expressive Shortcut Models
Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL
GenPO: Generative Diffusion Models Meet On-Policy Reinforcement Learning
Diffusion Self-Weighted Guidance for Offline Reinforcement Learning
Offline Guarded Safe Reinforcement Learning for Medical Treatment Optimization Strategies
PyTupli: A Scalable Infrastructure for Collaborative Offline Reinforcement Learning Projects
Efficient Online RL Fine Tuning with Offline Pre-trained Policy Only
Think-J: Learning to Think for Generative LLM-as-a-Judge
Unearthing Gems from Stones: Policy Optimization with Negative Sample Augmentation for LLM Reasoning
Your Offline Policy is Not Trustworthy: Bilevel Reinforcement Learning for Sequential Portfolio Optimization
Prior-Guided Diffusion Planning for Offline Reinforcement Learning
ImagineBench: Evaluating Reinforcement Learning with Large Language Model Rollouts
Reinforcement Learning for Individual Optimal Policy from Heterogeneous Data
Feasibility-Aware Pessimistic Estimation: Toward Long-Horizon Safety in Offline RL
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.