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
379 papers, page 7 of 8
- ICLR 2025Robust Transfer of Safety-Constrained Reinforcement Learning Agents
- ICLR 2025RTDiff: Reverse Trajectory Synthesis via Diffusion for Offline Reinforcement Learning
- ICLR 2025Safety Representations for Safer Policy Learning
- ICLR 2025Safety-Prioritizing Curricula for Constrained Reinforcement Learning
- ICLR 2025Sail into the Headwind: Alignment via Robust Rewards and Dynamic Labels against Reward Hacking
- ICLR 2025Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction
- ICLR 2025Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining
- ICLR 2025Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement Learning
- ICLR 2025Seeing Eye to AI: Human Alignment via Gaze-Based Response Rewards for Large Language Models
- ICLR 2025Select before Act: Spatially Decoupled Action Repetition for Continuous Control
- ICLR 2025SELF-EVOLVED REWARD LEARNING FOR LLMS
- ICLR 2025Self-Improving Robust Preference Optimization
- ICLR 2025Self-Play Preference Optimization for Language Model Alignment
- ICLR 2025Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models
- ICLR 2025Semantic Temporal Abstraction via Vision-Language Model Guidance for Efficient Reinforcement Learning
- ICLR 2025SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation
- ICLR 2025Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning
- ICLR 2025SeRA: Self-Reviewing and Alignment of LLMs using Implicit Reward Margins
- ICLR 2025SFESS: Score Function Estimators for $k$-Subset Sampling
- ICLR 2025SFS: Smarter Code Space Search improves LLM Inference Scaling
- ICLR 2025Sharpness-Aware Black-Box Optimization
- ICLR 2025SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
- ICLR 2025Simple, Good, Fast: Self-Supervised World Models Free of Baggage
- ICLR 2025Simplifying Deep Temporal Difference Learning
- ICLR 2025SmartRAG: Jointly Learn RAG-Related Tasks From the Environment Feedback
- ICLR 2025Solving hidden monotone variational inequalities with surrogate losses
- ICLR 2025SOO-Bench: Benchmarks for Evaluating the Stability of Offline Black-Box Optimization
- ICLR 2025Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models
- ICLR 2025SRSA: Skill Retrieval and Adaptation for Robotic Assembly Tasks
- ICLR 2025Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation
- ICLR 2025Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
- ICLR 2025Statistical Tractability of Off-policy Evaluation of History-dependent Policies in POMDPs
- ICLR 2025Strategist: Self-improvement of LLM Decision Making via Bi-Level Tree Search
- ICLR 2025Student-Informed Teacher Training
- ICLR 2025Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning
- ICLR 2025Subtask-Aware Visual Reward Learning from Segmented Demonstrations
- ICLR 2025Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
- ICLR 2025Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search
- ICLR 2025Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
- ICLR 2025Taming Overconfidence in LLMs: Reward Calibration in RLHF
- ICLR 2025Temporal Difference Learning: Why It Can Be Fast and How It Will Be Faster
- ICLR 2025The "Law'' of the Unconscious Contrastive Learner: Probabilistic Alignment of Unpaired Modalities
- ICLR 2025The Value of Sensory Information to a Robot
- ICLR 2025ToolGen: Unified Tool Retrieval and Calling via Generation
- ICLR 2025TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning
- ICLR 2025Toward Efficient Multi-Agent Exploration With Trajectory Entropy Maximization
- ICLR 2025Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers
- ICLR 2025Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning
- ICLR 2025Towards Federated RLHF with Aggregated Client Preference for LLMs
- ICLR 2025Towards General-Purpose Model-Free 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.