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

784 papers, page 9 of 16

401. NeurIPS 2025Multimodal Bandits: Regret Lower Bounds and Optimal Algorithms
402. NeurIPS 2025MURKA: Multi-Reward Reinforcement Learning with Knowledge Alignment for Optimization Tasks
403. NeurIPS 2025MyoChallenge 2024: A New Benchmark for Physiological Dexterity and Agility in Bionic Humans
404. NeurIPS 2025Nabla-R2D3: Effective and Efficient 3D Diffusion Alignment with 2D Rewards
405. NeurIPS 2025NAVIX: Scaling MiniGrid Environments with JAX
406. NeurIPS 2025Near-Optimal Sample Complexity for Online Constrained MDPs
407. NeurIPS 2025NeSyPr: Neurosymbolic Proceduralization For Efficient Embodied Reasoning
408. NeurIPS 2025Neural Combinatorial Optimization for Time Dependent Traveling Salesman Problem
409. NeurIPS 2025No Experts, No Problem: Avoidance Learning from Bad Demonstrations
410. NeurIPS 2025No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes
411. NeurIPS 2025NoisyGRPO: Incentivizing Multimodal CoT Reasoning via Noise Injection and Bayesian Estimation
412. NeurIPS 2025NoisyRollout: Reinforcing Visual Reasoning with Data Augmentation
413. NeurIPS 2025Non-convex entropic mean-field optimization via Best Response flow
414. NeurIPS 2025Non-rectangular Robust MDPs with Normed Uncertainty Sets
415. NeurIPS 2025Normalizing Flows are Capable Models for Continuous Control
416. NeurIPS 2025Novel Exploration via Orthogonality
417. NeurIPS 2025NS-Gym: A Comprehensive and Open-Source Simulation Framework for Non-Stationary Markov Decision Processes
418. NeurIPS 2025NTKMTL: Mitigating Task Imbalance in Multi-Task Learning from Neural Tangent Kernel Perspective
419. NeurIPS 2025Off-policy Reinforcement Learning with Model-based Exploration Augmentation
420. NeurIPS 2025Offline Actor-Critic for Average Reward MDPs
421. NeurIPS 2025Offline Goal-conditioned Reinforcement Learning with Quasimetric Representations
422. NeurIPS 2025Offline Guarded Safe Reinforcement Learning for Medical Treatment Optimization Strategies
423. NeurIPS 2025Offline imitation learning in $Q^\pi$-realizable MDPs without expert realizability
424. NeurIPS 2025Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization
425. NeurIPS 2025OMiSO: Adaptive optimization of state-dependent brain stimulation to shape neural population states
426. NeurIPS 2025Omni-R1: Reinforcement Learning for Omnimodal Reasoning via Two-System Collaboration
427. NeurIPS 2025On Evaluating Policies for Robust POMDPs
428. NeurIPS 2025On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning
429. NeurIPS 2025On the Convergence of Single-Timescale Actor-Critic
430. NeurIPS 2025On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization
431. NeurIPS 2025On the Global Optimality of Policy Gradient Methods in General Utility Reinforcement Learning
432. NeurIPS 2025On the Sample Complexity Bounds of Bilevel Reinforcement Learning
433. NeurIPS 2025On the Sample Complexity of Differentially Private Policy Optimization
434. NeurIPS 2025On-Policy Optimization with Group Equivalent Preference for Multi-Programming Language Understanding
435. NeurIPS 2025One Subgoal at a Time: Zero-Shot Generalization to Arbitrary Linear Temporal Logic Requirements in Multi-Task Reinforcement Learning
436. NeurIPS 2025Online Optimization for Offline Safe Reinforcement Learning
437. NeurIPS 2025Open Vision Reasoner: Transferring Linguistic Cognitive Behavior for Visual Reasoning
438. NeurIPS 2025Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
439. NeurIPS 2025Open-World Drone Active Tracking with Goal-Centered Rewards
440. NeurIPS 2025OpenVLThinker: Complex Vision-Language Reasoning via Iterative SFT-RL Cycles
441. NeurIPS 2025OPHR: Mastering Volatility Trading with Multi-Agent Deep Reinforcement Learning
442. NeurIPS 2025Optimal Dynamic Regret by Transformers for Non-Stationary Reinforcement Learning
443. NeurIPS 2025Optimal Regret Bounds via Low-Rank Structured Variation in Non-Stationary Reinforcement Learning
444. NeurIPS 2025Optimal Single-Policy Sample Complexity and Transient Coverage for Average-Reward Offline RL
445. NeurIPS 2025Optimizing Anytime Reasoning via Budget Relative Policy Optimization
446. NeurIPS 2025Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL
447. NeurIPS 2025Optimizing the Unknown: Black Box Bayesian Optimization with Energy-Based Model and Reinforcement Learning
448. NeurIPS 2025Option-aware Temporally Abstracted Value for Offline Goal-Conditioned Reinforcement Learning
449. NeurIPS 2025OrbitZoo: Real Orbital Systems Challenges for Reinforcement Learning
450. NeurIPS 2025ORIGAMISPACE: Benchmarking Multimodal LLMs in Multi-Step Spatial Reasoning with Mathematical Constraints

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.