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

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Showing 451–500 of 15113 papers

TitleStatusHype
MPCritic: A plug-and-play MPC architecture for reinforcement learningCode1
ReaRAG: Knowledge-guided Reasoning Enhances Factuality of Large Reasoning Models with Iterative Retrieval Augmented GenerationCode1
NeoRL-2: Near Real-World Benchmarks for Offline Reinforcement Learning with Extended Realistic ScenariosCode1
Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-TrainingCode1
Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical InvestigationCode1
TERL: Large-Scale Multi-Target Encirclement Using Transformer-Enhanced Reinforcement LearningCode1
Regulatory DNA sequence Design with Reinforcement LearningCode1
VisRL: Intention-Driven Visual Perception via Reinforced ReasoningCode1
Discrete Codebook World Models for Continuous ControlCode1
Reinforcement learning with combinatorial actions for coupled restless banditsCode1
VEM: Environment-Free Exploration for Training GUI Agent with Value Environment ModelCode1
Distilling Reinforcement Learning Algorithms for In-Context Model-Based PlanningCode1
Generating π-Functional Molecules Using STGG+ with Active LearningCode1
Reinforcement Learning for Dynamic Resource Allocation in Optical Networks: Hype or Hope?Code1
Learning to Sample Effective and Diverse Prompts for Text-to-Image GenerationCode1
Hierarchical Learning-based Graph Partition for Large-scale Vehicle Routing ProblemsCode1
DuoGuard: A Two-Player RL-Driven Framework for Multilingual LLM GuardrailsCode1
Analytical Lyapunov Function Discovery: An RL-based Generative ApproachCode1
GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic EnvironmentsCode1
SHARPIE: A Modular Framework for Reinforcement Learning and Human-AI Interaction ExperimentsCode1
Langevin Soft Actor-Critic: Efficient Exploration through Uncertainty-Driven Critic LearningCode1
xJailbreak: Representation Space Guided Reinforcement Learning for Interpretable LLM JailbreakingCode1
An Attentive Graph Agent for Topology-Adaptive Cyber DefenceCode1
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster trainingCode1
Co-Activation Graph Analysis of Safety-Verified and Explainable Deep Reinforcement Learning PoliciesCode1
Exploiting Hybrid Policy in Reinforcement Learning for Interpretable Temporal Logic ManipulationCode1
Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous InferenceCode1
RL-LLM-DT: An Automatic Decision Tree Generation Method Based on RL Evaluation and LLM EnhancementCode1
Entropy-Regularized Process Reward ModelCode1
Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement LearningCode1
Are Expressive Models Truly Necessary for Offline RL?Code1
Reinforcement Learning Policy as Macro Regulator Rather than Macro PlacerCode1
M^3PC: Test-time Model Predictive Control for Pretrained Masked Trajectory ModelCode1
Mind the Gap: Towards Generalizable Autonomous Penetration Testing via Domain Randomization and Meta-Reinforcement LearningCode1
AI-Driven Day-to-Day Route ChoiceCode1
Multi-Agent Environments for Vehicle Routing ProblemsCode1
LEDRO: LLM-Enhanced Design Space Reduction and Optimization for Analog CircuitsCode1
Doubly Mild Generalization for Offline Reinforcement LearningCode1
Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PCCode1
Zonal RL-RRT: Integrated RL-RRT Path Planning with Collision Probability and Zone ConnectivityCode1
Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision TransformersCode1
Online Intrinsic Rewards for Decision Making Agents from Large Language Model FeedbackCode1
Learning Successor Features the Simple WayCode1
A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics TasksCode1
Offline Reinforcement Learning with OOD State Correction and OOD Action SuppressionCode1
Leveraging Skills from Unlabeled Prior Data for Efficient Online ExplorationCode1
Reinforced Imitative Trajectory Planning for Urban Automated DrivingCode1
Sliding Puzzles Gym: A Scalable Benchmark for State Representation in Visual Reinforcement LearningCode1
Safety Filtering While Training: Improving the Performance and Sample Efficiency of Reinforcement Learning AgentsCode1
Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter EfficientCode1
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Benchmark Results

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