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

911 papers, page 9 of 19

401. ICLR 2026LearNAT: Learning NL2SQL with AST-guided Task Decomposition for Large Language Models
402. ICLR 2026Learning Correlated Reward Models: Statistical Barriers and Opportunities
403. ICLR 2026Learning Dynamics Feature Representation via Policy Attention for Dynamic Path Planning in Urban Road Networks
404. ICLR 2026Learning Efficient and Interpretable Multi-Agent Communication
405. ICLR 2026Learning from Algorithm Feedback: One-Shot SAT Solver Guidance with GNNs
406. ICLR 2026Learning from Synthetic Data Improves Multi-hop Reasoning
407. ICLR 2026Learning Massively Multitask World Models for Continuous Control
408. ICLR 2026Learning More with Less: A Dynamic Dual-Level Down-Sampling Framework for Efficient Policy Optimization
409. ICLR 2026Learning Nonlinear Causal Reductions to Explain Reinforcement Learning Policies
410. ICLR 2026Learning To Draft: Adaptive Speculative Decoding with Reinforcement Learning
411. ICLR 2026Learning to Generate Unit Test via Adversarial Reinforcement Learning
412. ICLR 2026Learning to Lie: Adversarial Attacks on Human-AI Teams and LLMs
413. ICLR 2026Learning to Orchestrate Agents in Natural Language with the Conductor
414. ICLR 2026Learning to Reason as Action Abstractions with Scalable Mid-Training RL
415. ICLR 2026Learning to Reason Efficiently with Discounted Reinforcement Learning
416. ICLR 2026Learning to Reason for Hallucination Span Detection
417. ICLR 2026Learning to Reason in Structured In-context Environments with Reinforcement Learning
418. ICLR 2026Learning to Reason over Continuous Tokens with Reinforcement Learning
419. ICLR 2026Learning to Reason without External Rewards
420. ICLR 2026Learning to summarize user information for personalized reinforcement learning from human feedback
421. ICLR 2026Learning What Reinforcement Learning Can't: Interleaved Online Fine-Tuning for Hardest Questions
422. ICLR 2026Less Is More: Clustered Cross-Covariance Control for Offline RL
423. ICLR 2026Leveraging Discrete Function Decomposability for Scientific Design
424. ICLR 2026Leveraging Explanation to Improve Generalization of Meta Reinforcement Learning
425. ICLR 2026Linking Process to Outcome: Conditional Reward Modeling for LLM Reasoning
426. ICLR 2026LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
427. ICLR 2026LLMs Must Think Thrice to Solve Executable Counterfactuals
428. ICLR 2026Local Reinforcement Learning with Action-Conditioned Root Mean Squared Q-Functions
429. ICLR 2026Long-Document QA with Chain-of-Structured-Thought and Fine-Tuned SLMs
430. ICLR 2026LongRLVR: Long-Context Reinforcement Learning Requires Verifiable Context Rewards
431. ICLR 2026LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning
432. ICLR 2026Look Back to Reason Forward: Revisitable Memory for Long-Context LLM Agents
433. ICLR 2026Look-ahead Reasoning with a Learned Model in Imperfect Information Games
434. ICLR 2026Lookahead Tree-Based Rollouts for Enhanced Trajectory-Level Exploration in Reinforcement Learning with Verifiable Rewards
435. ICLR 2026LoongRL: Reinforcement Learning for Advanced Reasoning over Long Contexts
436. ICLR 2026MAC-AMP: A Closed-Loop Multi-Agent Collaboration System for Multi-Objective Antimicrobial Peptide Design
437. ICLR 2026MAGE: Multi-scale Autoregressive Generation for Offline Reinforcement Learning
438. ICLR 2026MAGO: Beyond Fixed Hyperparameters with Multi-Objective Pareto Optimization for Hybrid LLM Reasoning
439. ICLR 2026Making Slow Thinking Faster: Compressing LLM Chain-of-Thought via Step Entropy
440. ICLR 2026MARC: Memory-Augmented RL Token Compression for Efficient Video Understanding
441. ICLR 2026Markovian Transformers for Informative Language Modeling
442. ICLR 2026MARS-Sep: Multimodal-Aligned Reinforced Sound Separation
443. ICLR 2026MARSHAL: Incentivizing Multi-Agent Reasoning via Self-Play with Strategic LLMs
444. ICLR 2026MARTI: A Framework for Multi-Agent LLM Systems Reinforced Training and Inference
445. ICLR 2026Masked Skill Token Training for Hierarchical Off-Dynamics Transfer
446. ICLR 2026Master Skill Learning with Policy-Grounded Synergy of LLM-based Reward Shaping and Exploring
447. ICLR 2026Mastering Sparse CUDA Generation through Pretrained Models and Deep Reinforcement Learning
448. ICLR 2026MATH-Beyond: A Benchmark for RL to Expand Beyond the Base Model
449. ICLR 2026Mathesis: Towards Formal Theorem Proving from Natural Languages
450. ICLR 2026Mean Flow Policy with Instantaneous Velocity Constraint for One-step Action Generation

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.