Reinforcement Learning papers, 2023–2026

Policy optimization, offline RL, and decision learning from interaction

Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 6,885 papers are tagged with this topic.

Key findings

Papers per year

Papers per venue

Counts by year and venue

Reinforcement Learning papers by year and venue
YearNeurIPSICLRICMLCVPRTotal
2023484233297561,070
2024466304356641,190
2025784379405721,640
20267609111,0212932,985

Representative papers

Spread across years and venues so every edition shows up

All Reinforcement Learning papers

6,885 papers, page 138 of 138

  1. NeurIPS 2023Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics
  2. NeurIPS 2023Towards robust and generalizable representations of extracellular data using contrastive learning
  3. NeurIPS 2023TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning
  4. NeurIPS 2023Train Hard, Fight Easy: Robust Meta Reinforcement Learning
  5. NeurIPS 2023Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning
  6. NeurIPS 2023Training Transitive and Commutative Multimodal Transformers with LoReTTa
  7. NeurIPS 2023Transportability for Bandits with Data from Different Environments
  8. NeurIPS 2023Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach
  9. NeurIPS 2023Trust Region-Based Safe Distributional Reinforcement Learning for Multiple Constraints
  10. NeurIPS 2023Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning
  11. NeurIPS 2023Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization
  12. NeurIPS 2023Uncertainty-Aware Instance Reweighting for Off-Policy Learning
  13. NeurIPS 2023Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning
  14. NeurIPS 2023Understanding Contrastive Learning via Distributionally Robust Optimization
  15. NeurIPS 2023Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL
  16. NeurIPS 2023Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective
  17. NeurIPS 2023Unsupervised Behavior Extraction via Random Intent Priors
  18. NeurIPS 2023Unsupervised Learning for Solving the Travelling Salesman Problem
  19. NeurIPS 2023Use perturbations when learning from explanations
  20. NeurIPS 2023Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies
  21. NeurIPS 2023Video Prediction Models as Rewards for Reinforcement Learning
  22. NeurIPS 2023VOCE: Variational Optimization with Conservative Estimation for Offline Safe Reinforcement Learning
  23. NeurIPS 2023VTaC: A Benchmark Dataset of Ventricular Tachycardia Alarms from ICU Monitors
  24. NeurIPS 2023Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies
  25. NeurIPS 2023Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research
  26. NeurIPS 2023Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets
  27. NeurIPS 2023WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts
  28. NeurIPS 2023Weakly Coupled Deep Q-Networks
  29. NeurIPS 2023Weitzman's Rule for Pandora's Box with Correlations
  30. NeurIPS 2023When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning
  31. NeurIPS 2023When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment
  32. NeurIPS 2023When is Agnostic Reinforcement Learning Statistically Tractable?
  33. NeurIPS 2023Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
  34. NeurIPS 2023Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization
  35. NeurIPS 2023Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis

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FAQ

How many Reinforcement Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
6,885 in total: 1,070 in 2023, 1,190 in 2024, 1,640 in 2025, 2,985 in 2026.
How many Reinforcement Learning papers are at NeurIPS 2026?
NeurIPS 2026 has 760 Reinforcement Learning papers, versus 784 the year before.
How many Reinforcement Learning papers are at ICLR 2026?
ICLR 2026 has 911 Reinforcement Learning papers, versus 379 the year before.
How many Reinforcement Learning papers are at ICML 2026?
ICML 2026 has 1,021 Reinforcement Learning papers, versus 405 the year before.
How many Reinforcement Learning papers are at CVPR 2026?
CVPR 2026 has 293 Reinforcement Learning papers, versus 72 the year before.
Which conference publishes the most Reinforcement Learning papers?
NeurIPS, with 2,494 papers from 2023 to 2026.