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
- Reinforcement Learning went from 1,070 papers in 2023 to 2,985 in 2026, roughly 2.8x in three years.
- NeurIPS publishes the most Reinforcement Learning work: 2,494 papers from 2023 to 2026, 36% of the four-venue total.
- The fastest-growing overlap is with Reasoning Models: papers tagged with both rose from 9 in 2023 to 437 in 2026.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 484 | 233 | 297 | 56 | 1,070 |
| 2024 | 466 | 304 | 356 | 64 | 1,190 |
| 2025 | 784 | 379 | 405 | 72 | 1,640 |
| 2026 | 760 | 911 | 1,021 | 293 | 2,985 |
Representative papers
Spread across years and venues so every edition shows up
- NeurIPS 2026\texttt{FEROM}: Frontier Endogenous Reveal-Order Marginal Policy Optimization for Masked Diffusion LMs
- ICML 2026$\text{DT}^\text{2}$: Decision-Targeted Digital Twins
- ICLR 2026$\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Textual Space
- CVPR 2026A Causal Marriage between VLM and IRM from Understanding to
- NeurIPS 2025$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
- ICML 2025A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
- ICLR 2025$\phi$-Update: A Class of Policy Update Methods with Policy Convergence Guarantee
- CVPR 2025All-Optical Nonlinear Diffractive Deep Network for Ultrafast Image Denoising
- NeurIPS 2024A Critical Evaluation of AI Feedback for Aligning Large Language Models
- ICML 2024${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
- ICLR 2024A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
- CVPR 2024DMR: Decomposed Multi-Modality Representations for Frames and Events Fusion in Visual Reinforcement Learning
- NeurIPS 2023“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization
- ICML 2023A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
- ICLR 2023$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games
- CVPR 2023"Seeing" Electric Network Frequency From Events
- NeurIPS 2026$\varphi$TD: Distributional Reinforcement Learning using Characteristic Functions
- ICML 2026$\textit{S}$-SPPO: Semantic-Calibrated Self-Play Preference Optimization
- ICLR 2026$AutoDrive\text{-}P^3$: Unified Chain of Perception–Prediction–Planning Thought via Reinforcement Fine-Tuning
- CVPR 2026AdaptVision Efficient Vision-Language Models via Adaptive Visual Acquisition
All Reinforcement Learning papers
2,079 papers, page 41 of 42
- ICML 2023Reinforcement Learning from Passive Data via Latent Intentions
- ICML 2023Reinforcement Learning in Low-rank MDPs with Density Features
- ICML 2023Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space
- ICML 2023Reinforcement Learning with History Dependent Dynamic Contexts
- ICML 2023ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs
- ICML 2023Reparameterized Policy Learning for Multimodal Trajectory Optimization
- ICML 2023Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
- ICML 2023Representation-Driven Reinforcement Learning
- ICML 2023Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
- ICML 2023Retrosynthetic Planning with Dual Value Networks
- ICML 2023Revisiting Bellman Errors for Offline Model Selection
- ICML 2023Revisiting Domain Randomization via Relaxed State-Adversarial Policy Optimization
- ICML 2023Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation
- ICML 2023Reward-Mixing MDPs with Few Latent Contexts are Learnable
- ICML 2023RLang: A Declarative Language for Describing Partial World Knowledge to Reinforcement Learning Agents
- ICML 2023Robust Collaborative Learning with Linear Gradient Overhead
- ICML 2023Robust Satisficing MDPs
- ICML 2023Robust Situational Reinforcement Learning in Face of Context Disturbances
- ICML 2023Robust Subtask Learning for Compositional Generalization
- ICML 2023Robustly Learning a Single Neuron via Sharpness
- ICML 2023Safe Offline Reinforcement Learning with Real-Time Budget Constraints
- ICML 2023SAM operates far from home: eigenvalue regularization as a dynamical phenomenon
- ICML 2023Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy Regimes
- ICML 2023Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
- ICML 2023Scalable Safe Policy Improvement via Monte Carlo Tree Search
- ICML 2023Scaling Laws for Reward Model Overoptimization
- ICML 2023Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning
- ICML 2023SeMAIL: Eliminating Distractors in Visual Imitation via Separated Models
- ICML 2023Semi-Offline Reinforcement Learning for Optimized Text Generation
- ICML 2023Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories
- ICML 2023Semiparametrically Efficient Off-Policy Evaluation in Linear Markov Decision Processes
- ICML 2023Set-membership Belief State-based Reinforcement Learning for POMDPs
- ICML 2023Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments
- ICML 2023Shortest Edit Path Crossover: A Theory-driven Solution to the Permutation Problem in Evolutionary Neural Architecture Search
- ICML 2023Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning
- ICML 2023Simplified Temporal Consistency Reinforcement Learning
- ICML 2023SNeRL: Semantic-aware Neural Radiance Fields for Reinforcement Learning
- ICML 2023Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learning
- ICML 2023STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning
- ICML 2023Stein Variational Goal Generation for adaptive Exploration in Multi-Goal Reinforcement Learning
- ICML 2023STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition
- ICML 2023StriderNet: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes
- ICML 2023Subequivariant Graph Reinforcement Learning in 3D Environments
- ICML 2023Supported Trust Region Optimization for Offline Reinforcement Learning
- ICML 2023Target-based Surrogates for Stochastic Optimization
- ICML 2023TGRL: An Algorithm for Teacher Guided Reinforcement Learning
- ICML 2023The Benefits of Model-Based Generalization in Reinforcement Learning
- ICML 2023The Dormant Neuron Phenomenon in Deep Reinforcement Learning
- ICML 2023The Optimal Approximation Factors in Misspecified Off-Policy Value Function Estimation
- ICML 2023The Regret of Exploration and the Control of Bad Episodes in Reinforcement Learning
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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.