{"total":50,"rows":[{"id":"2509.16117","title":"DiffusionNFT: Online Diffusion Reinforcement with Forward Process","created":"2025-09-19","cited_by_count":230,"area":"diffusion"},{"id":"2308.01557","title":"Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models","created":"2023-08-03","cited_by_count":161,"area":"diffusion"},{"id":"2305.20009","title":"Protein Design with Guided Discrete Diffusion","created":"2023-05-31","cited_by_count":157,"area":"diffusion"},{"id":"2402.15194","title":"Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control","created":"2024-02-23","cited_by_count":143,"area":"diffusion"},{"id":"2408.08252","title":"Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding","created":"2024-08-15","cited_by_count":136,"area":"diffusion"},{"id":"2209.03855","title":"SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion","created":"2022-09-08","cited_by_count":127,"area":"diffusion"},{"id":"2407.13734","title":"Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review","created":"2024-07-18","cited_by_count":98,"area":"diffusion"},{"id":"2501.09685","title":"Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and Review","created":"2025-01-16","cited_by_count":88,"area":"diffusion"},{"id":"2502.02150","title":"On the Guidance of Flow Matching","created":"2025-02-04","cited_by_count":45,"area":"diffusion"},{"id":"2407.01573","title":"Model-Based Diffusion for Trajectory Optimization","created":"2024-05-28","cited_by_count":32,"area":"diffusion"},{"id":"2412.07775","title":"Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets","created":"2024-12-10","cited_by_count":32,"area":"diffusion"},{"id":"2405.19673","title":"Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models","created":"2024-05-30","cited_by_count":25,"area":"diffusion"},{"id":"2412.17920","title":"Causal Composition Diffusion Model for Closed-loop Traffic Generation","created":"2024-12-23","cited_by_count":22,"area":"diffusion"},{"id":"2502.03686","title":"Variational Control for Guidance in Diffusion Models","created":"2025-02-06","cited_by_count":22,"area":"diffusion"},{"id":"2210.15629","title":"Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks","created":"2022-10-27","cited_by_count":20,"area":"diffusion"},{"id":"2501.06148","title":"From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training","created":"2025-01-10","cited_by_count":19,"area":"diffusion"},{"id":"2306.01804","title":"Extracting Reward Functions from Diffusion Models","created":"2023-06-01","cited_by_count":18,"area":"diffusion"},{"id":"2506.01320","title":"Psi-Sampler: Initial Particle Sampling for SMC-Based Inference-Time Reward Alignment in Score Models","created":"2025-06-02","cited_by_count":15,"area":"diffusion"},{"id":"2310.00311","title":"Efficient Planning with Latent Diffusion","created":"2023-09-30","cited_by_count":12,"area":"diffusion"},{"id":"2407.09024","title":"Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control","created":"2024-07-12","cited_by_count":12,"area":"diffusion"},{"id":"2309.05803","title":"Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models","created":"2023-09-11","cited_by_count":10,"area":"diffusion"},{"id":"2502.06401","title":"Habitizing Diffusion Planning for Efficient and Effective Decision Making","created":"2025-02-10","cited_by_count":7,"area":"diffusion"},{"id":"2307.16463","title":"Don't be so negative! Score-based Generative Modeling with Oracle-assisted Guidance","created":"2023-07-31","cited_by_count":6,"area":"diffusion"},{"id":"2410.10766","title":"Adaptive Diffusion Terrain Generator for Autonomous Uneven Terrain Navigation","created":"2024-10-14","cited_by_count":6,"area":"diffusion"},{"id":"2603.12893","title":"Finite Difference Flow Optimization for RL Post-Training of Text-to-Image Models","created":"2026-03-13","cited_by_count":5,"area":"diffusion"},{"id":"2605.23346","title":"Contrastive Distribution Matching for Amortized Sequential Monte Carlo in Discrete Diffusion","created":"2026-05-22","cited_by_count":5,"area":"diffusion"},{"id":"2509.17941","title":"ComposableNav: Instruction-Following Navigation in Dynamic Environments via Composable Diffusion","created":"2025-09-22","cited_by_count":4,"area":"diffusion"},{"id":"2509.23846","title":"Adversarial Diffusion for Robust Reinforcement Learning","created":"2025-09-28","cited_by_count":4,"area":"diffusion"},{"id":"2510.00502","title":"Diffusion Alignment as Variational Expectation-Maximization","created":"2025-10-01","cited_by_count":4,"area":"diffusion"},{"id":"2411.14913","title":"Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation","created":"2024-11-22","cited_by_count":3,"area":"diffusion"},{"id":"2509.21942","title":"Structural Information-based Hierarchical Diffusion for Offline Reinforcement Learning","created":"2025-09-26","cited_by_count":3,"area":"diffusion"},{"id":"2512.02019","title":"Diffusion-Augmented Markov Decision Processes for Maximum Entropy Reinforcement Learning","created":"2025-12-01","cited_by_count":3,"area":"diffusion"},{"id":"2602.18799","title":"Rethinking Preference Alignment for Diffusion Models with Classifier-Free Guidance","created":"2026-02-21","cited_by_count":3,"area":"diffusion"},{"id":"2606.15260","title":"Trust-Region Diffusion Policies for Massively Parallel On-Policy RL","created":"2026-06-13","cited_by_count":2,"area":"diffusion"},{"id":"2508.01192","title":"Unified Generation-Refinement Planning: Bridging Guided Flow Matching and Sampling-Based MPC for Social Navigation","created":"2025-08-02","cited_by_count":1,"area":"diffusion"},{"id":"2602.12229","title":"Diffusion Alignment Beyond KL: Variance Minimisation as Effective Policy Optimiser","created":"2026-02-12","cited_by_count":1,"area":"diffusion"},{"id":"2603.16151","title":"EFF-Grasp: Energy-Field Flow Matching for Physics-Aware Dexterous Grasp Generation","created":"2026-03-17","cited_by_count":1,"area":"diffusion"},{"id":"2607.14455","title":"Motion Planning with Model-Based Diffusion via Constraint Optimization and Adaptive Scheduling","created":"2026-07-16","cited_by_count":1,"area":"diffusion"},{"id":"2609.09905","title":"FlowCPO: A Unified Divergence View of Preference Alignment for Flow Models","created":"2026-09-09","cited_by_count":1,"area":"diffusion"},{"id":"2504.16858","title":"Planning with Diffusion Models for Target-Oriented Dialogue Systems","created":"2025-04-23","cited_by_count":0,"area":"diffusion"},{"id":"2510.03508","title":"D2 Actor Critic: Diffusion Actor Meets Distributional Critic","created":"2025-10-03","cited_by_count":0,"area":"diffusion"},{"id":"2605.24810","title":"Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning","created":"2026-05-24","cited_by_count":0,"area":"diffusion"},{"id":"2605.30553","title":"Destruction is a General Strategy to Learn Generation; Diffusion's Strength is to Take it Seriously; Exploration is the Future","created":"2026-05-28","cited_by_count":0,"area":"diffusion"},{"id":"2606.21014","title":"BayesFP: Posterior Estimation for Flow-Based Policies via Feynman-Kac Sampling","created":"2026-06-19","cited_by_count":0,"area":"diffusion"},{"id":"2607.14272","title":"Lyapunov Guidance: A Unified Framework for Stabilizing Generative Flows","created":"2026-07-15","cited_by_count":0,"area":"diffusion"},{"id":"2609.15123","title":"Refinement-based Flow Policy Optimization","created":"2026-09-14","cited_by_count":0,"area":"diffusion"},{"id":"2609.33164","title":"Notes on Generative Modeling for Feedback Control and Planning","created":"2026-09-27","cited_by_count":0,"area":"diffusion"},{"id":"2609.35924","title":"Grab a Coffee: Future-Aware Guidance for Discrete Diffusion with Compiled Objectives","created":"2026-09-28","cited_by_count":0,"area":"diffusion"},{"id":"2610.12848","title":"Reinforcement Learning via Fixed-point Flow Matching","created":"2026-10-09","cited_by_count":0,"area":"diffusion"},{"id":"2610.17266","title":"RL Post-Training Diffusion Language Models Along Their Own Generation Paths","created":"2026-10-12","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}