SOTAVerified

Reinforcement Learning (RL)

Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2401–2450 of 15113 papers

TitleStatusHype
Unleashing the Reasoning Potential of Pre-trained LLMs by Critique Fine-Tuning on One Problem—0
Critique-GRPO: Advancing LLM Reasoning with Natural Language and Numerical Feedback—0
Knowledge or Reasoning? A Close Look at How LLMs Think Across Domains—0
Trajectory First: A Curriculum for Discovering Diverse Policies—0
KDRL: Post-Training Reasoning LLMs via Unified Knowledge Distillation and Reinforcement Learning—0
SRPO: Enhancing Multimodal LLM Reasoning via Reflection-Aware Reinforcement Learning—0
Data-assimilated model-informed reinforcement learning—0
A Reinforcement Learning Approach for RIS-aided Fair Communications—0
DriveMind: A Dual-VLM based Reinforcement Learning Framework for Autonomous Driving—0
MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning—0
ARIA: Training Language Agents with Intention-Driven Reward Aggregation—0
Reinforcement Learning for Hanabi—0
How Much Backtracking is Enough? Exploring the Interplay of SFT and RL in Enhancing LLM Reasoning—0
Balancing Profit and Fairness in Risk-Based Pricing Markets—0
Reason-SVG: Hybrid Reward RL for Aha-Moments in Vector Graphics Generation—0
Mixed-R1: Unified Reward Perspective For Reasoning Capability in Multimodal Large Language ModelsCode0
ROAD: Responsibility-Oriented Reward Design for Reinforcement Learning in Autonomous Driving—0
MOFGPT: Generative Design of Metal-Organic Frameworks using Language ModelsCode0
Pangu DeepDiver: Adaptive Search Intensity Scaling via Open-Web Reinforcement Learning—0
Proxy Target: Bridging the Gap Between Discrete Spiking Neural Networks and Continuous Control—0
Diversity-Aware Policy Optimization for Large Language Model Reasoning—0
Grounded Reinforcement Learning for Visual Reasoning—0
Reinforcement Learning for Better Verbalized Confidence in Long-Form Generation—0
LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Trainin—0
Let's Reason Formally: Natural-Formal Hybrid Reasoning Enhances LLM's Math Capability—0
Hybrid Cross-domain Robust Reinforcement Learning—0
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization—0
Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data—0
DIP-R1: Deep Inspection and Perception with RL Looking Through and Understanding Complex Scenes—0
Fortune: Formula-Driven Reinforcement Learning for Symbolic Table Reasoning in Language Models—0
ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning—0
Measure gradients, not activations! Enhancing neuronal activity in deep reinforcement learning—0
Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners—0
Fine-Tuning Next-Scale Visual Autoregressive Models with Group Relative Policy Optimization—0
Contextual Integrity in LLMs via Reasoning and Reinforcement Learning—0
Grower-in-the-Loop Interactive Reinforcement Learning for Greenhouse Climate Control—0
Unsupervised Transcript-assisted Video Summarization and Highlight Detection—0
SAM-R1: Leveraging SAM for Reward Feedback in Multimodal Segmentation via Reinforcement Learning—0
FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control—0
Scaling Offline RL via Efficient and Expressive Shortcut Models—0
ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning—0
Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean-Field Games—0
A Provable Approach for End-to-End Safe Reinforcement Learning—0
Enhancing Study-Level Inference from Clinical Trial Papers via RL-based Numeric Reasoning—0
HDDLGym: A Tool for Studying Multi-Agent Hierarchical Problems Defined in HDDL with OpenAI GymCode0
Maximizing Confidence Alone Improves Reasoning—0
Decomposing Elements of Problem Solving: What "Math" Does RL Teach?Code0
SOReL and TOReL: Two Methods for Fully Offline Reinforcement LearningCode0
When Does Neuroevolution Outcompete Reinforcement Learning in Transfer Learning Tasks?Code0
Rendering-Aware Reinforcement Learning for Vector Graphics Generation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PPGMean Normalized Performance0.76—Unverified
2PPOMean Normalized Performance0.58—Unverified