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

2,985 papers, page 10 of 60

451. ICLR 2026DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning
452. ICLR 2026DeepEyesV2: Toward Agentic Multimodal Model
453. ICLR 2026DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning
454. ICLR 2026DeepRAG: Thinking to Retrieve Step by Step for Large Language Models
455. ICLR 2026DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search
456. ICLR 2026Deft Scheduling of Dynamic Cloud Workflows with Varying Deadlines via Mixture-of-Experts
457. ICLR 2026DELTA-Code: How RL Unlocks and Transfers New Programming Algorithms in LLMs
458. ICLR 2026DemoGrasp: Universal Dexterous Grasping from a Single Demonstration
459. ICLR 2026Demystifying Emergent Exploration in Goal-Conditioned RL
460. ICLR 2026DenseGRPO: From Sparse to Dense Reward for Flow Matching Model Alignment
461. ICLR 2026DePO: Demonstration-guided Policy Optimization for Molecular Optimization
462. ICLR 2026Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
463. ICLR 2026Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models
464. ICLR 2026Dichotomous Diffusion Policy Optimization
465. ICLR 2026Differentiable Model Predictive Control on the GPU
466. ICLR 2026DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation
467. ICLR 2026Diffusion Alignment as Variataional Expectation-Maximization
468. ICLR 2026Diffusion Blend: Inference-Time Multi-Preference Alignment for Diffusion Models
469. ICLR 2026Diffusion Fine-Tuning via Reparameterized Policy Gradient of the Soft Q-Function
470. ICLR 2026DiffusionNFT: Online Diffusion Reinforcement with Forward Process
471. ICLR 2026Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approach
472. ICLR 2026Discovering Diverse Behaviors via Temporal Contrastive Learning
473. ICLR 2026Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
474. ICLR 2026Discrete Diffusion for Reflective Vision-Language-Action Models in Autonomous Driving
475. ICLR 2026Discrete Variational Autoencoding via Policy Search
476. ICLR 2026Disentangling Length Bias in Preference Learning via Response-Conditioned Modeling
477. ICLR 2026Displacement-Resistant Extensions of DPO with Nonconvex $f$-Divergences
478. ICLR 2026Distributional value gradients for stochastic environments
479. ICLR 2026Distributionally Robust Cooperative Multi-agent Reinforcement Learning with Value Factorization
480. ICLR 2026Distributions as Actions: A Unified Framework for Diverse Action Spaces
481. ICLR 2026DIVA-GRPO: Enhancing Multimodal Reasoning through Difficulty-Adaptive Variant Advantage
482. ICLR 2026DiVE-k: DIFFERENTIAL VISUAL REASONING FOR FINE-GRAINED IMAGE RECOGNITION
483. ICLR 2026Diversity-Enhanced Reasoning for Subjective Questions
484. ICLR 2026Diversity-Incentivized Exploration for Versatile Reasoning
485. ICLR 2026Divide, Harmonize, Then Conquer It: Shooting Multi-Commodity Flow Problems with Multimodal Language Models
486. ICLR 2026Do LLM Agents Know How to Ground, Recover, and Assess? Evaluating Epistemic Competence in Information-Seeking Agents
487. ICLR 2026Do Not Let Low-Probability Tokens Over-Dominate in RL for LLMs
488. ICLR 2026Doctor-R1: Mastering Clinical Inquiry with Experiential Agentic Reinforcement Learning
489. ICLR 2026Does “Do Differentiable Simulators Give Better Policy Gradients?” Give Better Policy Gradients?
490. ICLR 2026Don't Just Fine-tune the Agent, Tune the Environment
491. ICLR 2026Don't Settle Too Early: Self-Reflective Remasking for Diffusion Language Models
492. ICLR 2026DOPPLER: Dual-Policy Learning for Device Assignment in Asynchronous Dataflow Graphs
493. ICLR 2026DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty
494. ICLR 2026DriveAgent-R1: Advancing VLM-based Autonomous Driving with Active Perception and Hybrid Thinking
495. ICLR 2026DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization
496. ICLR 2026Dual Goal Representations
497. ICLR 2026Dual-Objective Reinforcement Learning with Novel Hamilton-Jacobi-Bellman Formulations
498. ICLR 2026Dual-Robust Cross-Domain Offline Reinforcement Learning Against Dynamics Shifts
499. ICLR 2026DUET: Optimizing LLM Training Data Mixtures via Noisy Feedback from Unseen, Downstream Evaluation Tasks
500. ICLR 2026DuPO: Enabling Reliable Self-Verification via Dual Preference Optimization

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.