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

304 papers, page 5 of 7

201. ICLR 2024Provable Reward-Agnostic Preference-Based Reinforcement Learning
202. ICLR 2024Provably Efficient CVaR RL in Low-rank MDPs
203. ICLR 2024Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback
204. ICLR 2024Provably Efficient UCB-type Algorithms For Learning Predictive State Representations
205. ICLR 2024Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning
206. ICLR 2024Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification
207. ICLR 2024Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
208. ICLR 2024Query-Policy Misalignment in Preference-Based Reinforcement Learning
209. ICLR 2024RAIN: Your Language Models Can Align Themselves without Finetuning
210. ICLR 2024RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering
211. ICLR 2024Reasoning with Latent Diffusion in Offline Reinforcement Learning
212. ICLR 2024Reclaiming the Source of Programmatic Policies: Programmatic versus Latent Spaces
213. ICLR 2024Reconciling Spatial and Temporal Abstractions for Goal Representation
214. ICLR 2024Reinforcement Symbolic Regression Machine
215. ICLR 2024Replay across Experiments: A Natural Extension of Off-Policy RL
216. ICLR 2024Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL
217. ICLR 2024Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization
218. ICLR 2024Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization
219. ICLR 2024REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes
220. ICLR 2024Reverse Forward Curriculum Learning for Extreme Sample and Demo Efficiency
221. ICLR 2024Revisiting Data Augmentation in Deep Reinforcement Learning
222. ICLR 2024Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages
223. ICLR 2024Reward Design for Justifiable Sequential Decision-Making
224. ICLR 2024Reward Model Ensembles Help Mitigate Overoptimization
225. ICLR 2024Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning
226. ICLR 2024Reward-Free Curricula for Training Robust World Models
227. ICLR 2024RingAttention with Blockwise Transformers for Near-Infinite Context
228. ICLR 2024RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment
229. ICLR 2024RLIF: Interactive Imitation Learning as Reinforcement Learning
230. ICLR 2024Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula
231. ICLR 2024Robust Model Based Reinforcement Learning Using $\mathcal{L}_1$ Adaptive Control
232. ICLR 2024S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic
233. ICLR 2024Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
234. ICLR 2024Safe RLHF: Safe Reinforcement Learning from Human Feedback
235. ICLR 2024SafeDreamer: Safe Reinforcement Learning with World Models
236. ICLR 2024SALMON: Self-Alignment with Instructable Reward Models
237. ICLR 2024Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks
238. ICLR 2024Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
239. ICLR 2024Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
240. ICLR 2024Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
241. ICLR 2024Sample-Efficient Multi-Agent RL: An Optimization Perspective
242. ICLR 2024Sample-Efficient Quality-Diversity by Cooperative Coevolution
243. ICLR 2024Score Models for Offline Goal-Conditioned Reinforcement Learning
244. ICLR 2024Score Regularized Policy Optimization through Diffusion Behavior
245. ICLR 2024SEABO: A Simple Search-Based Method for Offline Imitation Learning
246. ICLR 2024Searching for High-Value Molecules Using Reinforcement Learning and Transformers
247. ICLR 2024Selective Visual Representations Improve Convergence and Generalization for Embodied AI
248. ICLR 2024Simple Hierarchical Planning with Diffusion
249. ICLR 2024Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning
250. ICLR 2024Skill or Luck? Return Decomposition via Advantage Functions

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.