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

1,640 papers, page 30 of 33

1451. NeurIPS 2025SAM-R1: Leveraging SAM for Reward Feedback in Multimodal Segmentation via Reinforcement Learning
1452. NeurIPS 2025Sample Complexity of Distributionally Robust Average-Reward Reinforcement Learning
1453. NeurIPS 2025Sample-Efficient Tabular Self-Play for Offline Robust Reinforcement Learning
1454. NeurIPS 2025SAMPO: Scale-wise Autoregression with Motion Prompt for Generative World Models
1455. NeurIPS 2025SATURN: SAT-based Reinforcement Learning to Unleash LLMs Reasoning
1456. NeurIPS 2025Scaffolding Dexterous Manipulation with Vision-Language Models
1457. NeurIPS 2025Scalable Exploration via Ensemble++
1458. NeurIPS 2025Scalable Policy-Based RL Algorithms for POMDPs
1459. NeurIPS 2025Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization
1460. NeurIPS 2025Scaling Offline RL via Efficient and Expressive Shortcut Models
1461. NeurIPS 2025Scaling RL to Long Videos
1462. NeurIPS 2025SceneDesigner: Controllable Multi-Object Image Generation with 9-DoF Pose Manipulation
1463. NeurIPS 2025Scent of Knowledge: Optimizing Search-Enhanced Reasoning with Information Foraging
1464. NeurIPS 2025SE-GUI: Enhancing Visual Grounding for GUI Agents via Self-Evolutionary Reinforcement Learning
1465. NeurIPS 2025Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning
1466. NeurIPS 2025SEEA-R1: Tree-Structured Reinforcement Fine-Tuning for Self-Evolving Embodied Agents
1467. NeurIPS 2025Seeing is Believing? Mitigating OCR Hallucinations in Multimodal Large Language Models
1468. NeurIPS 2025Seeing the Arrow of Time in Large Multimodal Models
1469. NeurIPS 2025Seeing through Uncertainty: Robust Task-Oriented Optimization in Visual Navigation
1470. NeurIPS 2025Seg-VAR:Image Segmentation with Visual Autoregressive Modeling
1471. NeurIPS 2025Segment Policy Optimization: Effective Segment-Level Credit Assignment in RL for Large Language Models
1472. NeurIPS 2025Self-Adapting Language Models
1473. NeurIPS 2025Self-Challenging Language Model Agents
1474. NeurIPS 2025Self-Guided Hierarchical Exploration for Generalist Foundation Model Web Agents
1475. NeurIPS 2025Self-Improving Embodied Foundation Models
1476. NeurIPS 2025Self-Verifying Reflection Helps Transformers with CoT Reasoning
1477. NeurIPS 2025Selftok-Zero: Reinforcement Learning for Visual Generation via Discrete and Autoregressive Visual Tokens
1478. NeurIPS 2025Semantic-guided Diverse Decoding for Large Language Model
1479. NeurIPS 2025Semi-off-Policy Reinforcement Learning for Vision-Language Slow-Thinking Reasoning
1480. NeurIPS 2025Sequential Attention-based Sampling for Histopathological Analysis
1481. NeurIPS 2025Sequential Monte Carlo for Policy Optimization in Continuous POMDPs
1482. NeurIPS 2025Sequential Multi-Agent Dynamic Algorithm Configuration
1483. NeurIPS 2025SeRL: Self-play Reinforcement Learning for Large Language Models with Limited Data
1484. NeurIPS 2025Sharp Analysis for KL-Regularized Contextual Bandits and RLHF
1485. NeurIPS 2025Sharp Gap-Dependent Variance-Aware Regret Bounds for Tabular MDPs
1486. NeurIPS 2025Shift Before You Learn: Enabling Low-Rank Representations in Reinforcement Learning
1487. NeurIPS 2025ShiQ: Bringing back Bellman to LLMs
1488. NeurIPS 2025ShorterBetter: Guiding Reasoning Models to Find Optimal Inference Length for Efficient Reasoning
1489. NeurIPS 2025Simultaneous Statistical Inference for Off-Policy Evaluation in Reinforcement Learning
1490. NeurIPS 2025Skill-Driven Neurosymbolic State Abstractions
1491. NeurIPS 2025Social World Model-Augmented Mechanism Design Policy Learning
1492. NeurIPS 2025Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling
1493. NeurIPS 2025Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics
1494. NeurIPS 2025SOMBRL: Scalable and Optimistic Model-Based RL
1495. NeurIPS 2025SonoGym: High Performance Simulation for Challenging Surgical Tasks with Robotic Ultrasound
1496. NeurIPS 2025SORTeD Rashomon Sets of Sparse Decision Trees: Anytime Enumeration
1497. NeurIPS 2025Spatial-Aware Decision-Making with Ring Attractors in Reinforcement Learning Systems
1498. NeurIPS 2025SPC: Evolving Self-Play Critic via Adversarial Games for LLM Reasoning
1499. NeurIPS 2025Spectral Learning for Infinite-Horizon Average-Reward POMDPs
1500. NeurIPS 2025SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer

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.