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
6,885 papers, page 138 of 138
- NeurIPS 2023Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics
- NeurIPS 2023Towards robust and generalizable representations of extracellular data using contrastive learning
- NeurIPS 2023TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning
- NeurIPS 2023Train Hard, Fight Easy: Robust Meta Reinforcement Learning
- NeurIPS 2023Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning
- NeurIPS 2023Training Transitive and Commutative Multimodal Transformers with LoReTTa
- NeurIPS 2023Transportability for Bandits with Data from Different Environments
- NeurIPS 2023Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach
- NeurIPS 2023Trust Region-Based Safe Distributional Reinforcement Learning for Multiple Constraints
- NeurIPS 2023Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning
- NeurIPS 2023Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization
- NeurIPS 2023Uncertainty-Aware Instance Reweighting for Off-Policy Learning
- NeurIPS 2023Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning
- NeurIPS 2023Understanding Contrastive Learning via Distributionally Robust Optimization
- NeurIPS 2023Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL
- NeurIPS 2023Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective
- NeurIPS 2023Unsupervised Behavior Extraction via Random Intent Priors
- NeurIPS 2023Unsupervised Learning for Solving the Travelling Salesman Problem
- NeurIPS 2023Use perturbations when learning from explanations
- NeurIPS 2023Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies
- NeurIPS 2023Video Prediction Models as Rewards for Reinforcement Learning
- NeurIPS 2023VOCE: Variational Optimization with Conservative Estimation for Offline Safe Reinforcement Learning
- NeurIPS 2023VTaC: A Benchmark Dataset of Ventricular Tachycardia Alarms from ICU Monitors
- NeurIPS 2023Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies
- NeurIPS 2023Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research
- NeurIPS 2023Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets
- NeurIPS 2023WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts
- NeurIPS 2023Weakly Coupled Deep Q-Networks
- NeurIPS 2023Weitzman's Rule for Pandora's Box with Correlations
- NeurIPS 2023When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning
- NeurIPS 2023When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment
- NeurIPS 2023When is Agnostic Reinforcement Learning Statistically Tractable?
- NeurIPS 2023Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
- NeurIPS 2023Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization
- NeurIPS 2023Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis
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.