Reinforcement Learning papers, 2023–2026

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.

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 119 of 138

5901. ICLR 2023Causal Confusion and Reward Misidentification in Preference-Based Reward Learning
5902. ICLR 2023Causal Imitation Learning via Inverse Reinforcement Learning
5903. ICLR 2023Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication
5904. ICLR 2023CFlowNets: Continuous Control with Generative Flow Networks
5905. ICLR 2023Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning
5906. ICLR 2023Choreographer: Learning and Adapting Skills in Imagination
5907. ICLR 2023CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning
5908. ICLR 2023Composing Task Knowledge With Modular Successor Feature Approximators
5909. ICLR 2023Confidence-Conditioned Value Functions for Offline Reinforcement Learning
5910. ICLR 2023Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization
5911. ICLR 2023Critic Sequential Monte Carlo
5912. ICLR 2023Curriculum-based Co-design of Morphology and Control of Voxel-based Soft Robots
5913. ICLR 2023DaxBench: Benchmarking Deformable Object Manipulation with Differentiable Physics
5914. ICLR 2023Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games
5915. ICLR 2023Decision S4: Efficient Sequence-Based RL via State Spaces Layers
5916. ICLR 2023Decision Transformer under Random Frame Dropping
5917. ICLR 2023Deep Generative Symbolic Regression
5918. ICLR 2023Deep Reinforcement Learning for Cost-Effective Medical Diagnosis
5919. ICLR 2023DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems
5920. ICLR 2023DexDeform: Dexterous Deformable Object Manipulation with Human Demonstrations and Differentiable Physics
5921. ICLR 2023Dichotomy of Control: Separating What You Can Control from What You Cannot
5922. ICLR 2023DiffMimic: Efficient Motion Mimicking with Differentiable Physics
5923. ICLR 2023Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning
5924. ICLR 2023Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning
5925. ICLR 2023Discovering Generalizable Multi-agent Coordination Skills from Multi-task Offline Data
5926. ICLR 2023Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality
5927. ICLR 2023Distributional Meta-Gradient Reinforcement Learning
5928. ICLR 2023Does Zero-Shot Reinforcement Learning Exist?
5929. ICLR 2023Dynamic Update-to-Data Ratio: Minimizing World Model Overfitting
5930. ICLR 2023Efficient Deep Reinforcement Learning Requires Regulating Overfitting
5931. ICLR 2023Efficient Offline Policy Optimization with a Learned Model
5932. ICLR 2023Efficient Planning in a Compact Latent Action Space
5933. ICLR 2023Efficiently Computing Nash Equilibria in Adversarial Team Markov Games
5934. ICLR 2023Emergence of Maps in the Memories of Blind Navigation Agents
5935. ICLR 2023ERL-Re$^2$: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation
5936. ICLR 2023ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret
5937. ICLR 2023EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model
5938. ICLR 2023Evaluating Long-Term Memory in 3D Mazes
5939. ICLR 2023Evolving Populations of Diverse RL Agents with MAP-Elites
5940. ICLR 2023Explaining RL Decisions with Trajectories
5941. ICLR 2023Extreme Q-Learning: MaxEnt RL without Entropy
5942. ICLR 2023Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems
5943. ICLR 2023Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games
5944. ICLR 2023FluidLab: A Differentiable Environment for Benchmarking Complex Fluid Manipulation
5945. ICLR 2023From $t$-SNE to UMAP with contrastive learning
5946. ICLR 2023From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data
5947. ICLR 2023Generalize Learned Heuristics to Solve Large-scale Vehicle Routing Problems in Real-time
5948. ICLR 2023Generating Diverse Cooperative Agents by Learning Incompatible Policies
5949. ICLR 2023Generative Augmented Flow Networks
5950. ICLR 2023GFlowNets and variational inference

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.