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

1,070 papers, page 11 of 22

  1. ICML 2023Quantile Credit Assignment
  2. ICML 2023Quantum Policy Gradient Algorithm with Optimized Action Decoding
  3. ICML 2023RACE: Improve Multi-Agent Reinforcement Learning with Representation Asymmetry and Collaborative Evolution
  4. ICML 2023Reachability-Aware Laplacian Representation in Reinforcement Learning
  5. ICML 2023Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents
  6. ICML 2023Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
  7. ICML 2023Reinforcement Learning Can Be More Efficient with Multiple Rewards
  8. ICML 2023Reinforcement Learning from Passive Data via Latent Intentions
  9. ICML 2023Reinforcement Learning in Low-rank MDPs with Density Features
  10. ICML 2023Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space
  11. ICML 2023Reinforcement Learning with History Dependent Dynamic Contexts
  12. ICML 2023ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs
  13. ICML 2023Reparameterized Policy Learning for Multimodal Trajectory Optimization
  14. ICML 2023Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
  15. ICML 2023Representation-Driven Reinforcement Learning
  16. ICML 2023Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
  17. ICML 2023Retrosynthetic Planning with Dual Value Networks
  18. ICML 2023Revisiting Bellman Errors for Offline Model Selection
  19. ICML 2023Revisiting Domain Randomization via Relaxed State-Adversarial Policy Optimization
  20. ICML 2023Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation
  21. ICML 2023Reward-Mixing MDPs with Few Latent Contexts are Learnable
  22. ICML 2023RLang: A Declarative Language for Describing Partial World Knowledge to Reinforcement Learning Agents
  23. ICML 2023Robust Collaborative Learning with Linear Gradient Overhead
  24. ICML 2023Robust Satisficing MDPs
  25. ICML 2023Robust Situational Reinforcement Learning in Face of Context Disturbances
  26. ICML 2023Robust Subtask Learning for Compositional Generalization
  27. ICML 2023Robustly Learning a Single Neuron via Sharpness
  28. ICML 2023Safe Offline Reinforcement Learning with Real-Time Budget Constraints
  29. ICML 2023SAM operates far from home: eigenvalue regularization as a dynamical phenomenon
  30. ICML 2023Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy Regimes
  31. ICML 2023Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
  32. ICML 2023Scalable Safe Policy Improvement via Monte Carlo Tree Search
  33. ICML 2023Scaling Laws for Reward Model Overoptimization
  34. ICML 2023Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning
  35. ICML 2023SeMAIL: Eliminating Distractors in Visual Imitation via Separated Models
  36. ICML 2023Semi-Offline Reinforcement Learning for Optimized Text Generation
  37. ICML 2023Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories
  38. ICML 2023Semiparametrically Efficient Off-Policy Evaluation in Linear Markov Decision Processes
  39. ICML 2023Set-membership Belief State-based Reinforcement Learning for POMDPs
  40. ICML 2023Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments
  41. ICML 2023Shortest Edit Path Crossover: A Theory-driven Solution to the Permutation Problem in Evolutionary Neural Architecture Search
  42. ICML 2023Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning
  43. ICML 2023Simplified Temporal Consistency Reinforcement Learning
  44. ICML 2023SNeRL: Semantic-aware Neural Radiance Fields for Reinforcement Learning
  45. ICML 2023Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning
  46. ICML 2023STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning
  47. ICML 2023Stein Variational Goal Generation for adaptive Exploration in Multi-Goal Reinforcement Learning
  48. ICML 2023STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition
  49. ICML 2023StriderNet: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes
  50. ICML 2023Subequivariant Graph Reinforcement Learning in 3D Environments

Ask about this trend from Claude or Cursor

Connect the Paperlist MCP and your assistant can pull the numbers on this page while you draft a survey, pick a direction or plan a submission: papers per year and venue, growth, the fastest-rising sub-themes and representative papers, shaped around your question.

Copy this prompt into your assistant

Use paperlist to show how Reinforcement Learning papers grew at NeurIPS from 2023 to 2026, and which year jumped the most.

Tool the assistant calls: get_topic_stats {"topic": "reinforcement-learning"}

Set up Paperlist MCP in two minutes (Claude Code, Cursor, Codex, ChatGPT)

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.