mlsanityData to 7 Oct 2026

From Noise to Control: Parameterized Diffusion Policies

arXiv 2606.00336 ↗First posted 29 May 2026cs.AI cs.LGcited by 0

On the map: Diffusion models → Diffusion and flow policies for robotics

Abstract (arXiv)

We propose Parameterized Diffusion Policy (PDP), a framework for learning diffusion policies conditioned on low-dimensional, continuous parameters embedded in a learned behavior manifold. By constructing this manifold so that distances between latent representations reflect the semantic similarity between physical trajectories, we transform diffusion from a mechanism for stochastic diversity into a precise and optimizable tool for behavior steering. Our approach enables smooth interpolation between known strategies and efficient adaptation to novel constraints without updating policy weights. We demonstrate that PDP significantly improves adaptation performance on complex multimodal benchmarks in both simulated and real-robot experiments compared to standard diffusion policies, particularly in scenarios requiring the synthesis of novel behaviors.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models. Builds on 57 of its 66 references that are in the map. First posted on arXiv 29 May 2026.

Builds on

57 of 66 references.

Closest ancestors · 23

Same direction, newest first

  1. 2025Diffusion Models for Reinforcement Learning: Foundations, Taxonomy, and Development14 Oct
  2. 2025Reinforcement Learning with Discrete Diffusion Policies for Combinatorial Action Spaces26 Sep
  3. 2025ADPro: a Test-time Adaptive Diffusion Policy via Manifold-constrained Denoising and Task-aware Initialization for Robotic Manipulation8 Aug
  4. 2025Steering Your Diffusion Policy with Latent Space Reinforcement Learning18 Jun
  5. 2025DiffusionRL: Efficient Training of Diffusion Policies for Robotic Grasping Using RL-Adapted Large-Scale Datasets24 May
  6. 2025Efficient Task-specific Conditional Diffusion Policies: Shortcut Model Acceleration and SO(3) Optimization14 Apr
  7. 2025Diffusion Models for Robotic Manipulation: A Survey11 Apr
  8. 2025Offline Reinforcement Learning with Discrete Diffusion Skills26 Mar
  9. 2024Discrete Policy: Learning Disentangled Action Space for Multi-Task Robotic Manipulation27 Sep
  10. 2024Forward KL Regularized Preference Optimization for Aligning Diffusion Policies9 Sep
  11. 2024Streaming Diffusion Policy: Fast Policy Synthesis with Variable Noise Diffusion Models7 Jun
  12. 2024Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient2 Jun
11 more
  1. 2024Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization25 May
  2. 2024Policy-Guided Diffusion9 Apr
  3. 2024Behavior Generation with Latent Actions5 Mar
  4. 2024Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction Following9 Feb
  5. 2023PlayFusion: Skill Acquisition via Diffusion from Language-Annotated Play7 Dec
  6. 2023Diffusion Models for Reinforcement Learning: A Survey2 Nov
  7. 2023Efficient Diffusion Policies for Offline Reinforcement Learning31 May
  8. 2023Training Diffusion Models with Reinforcement Learning22 May
  9. 2023Goal-Conditioned Imitation Learning using Score-based Diffusion Policies5 Apr
  10. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusion7 Mar
  11. 2022Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning12 Aug

Other references · 34

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  3. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  4. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  5. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  6. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  7. 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 2,994
  8. 2017FiLM: Visual Reasoning with a General Conditioning Layercited by 2,286
  9. 2022Planning with Diffusion for Flexible Behavior Synthesiscited by 1,023
  10. 2021What Matters in Learning from Offline Human Demonstrations for Robot Manipulationcited by 699
  11. 2023Learning Universal Policies via Text-Guided Video Generationcited by 506
  12. 2021Implicit Behavioral Cloningcited by 442
22 more
  1. 2019Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learningcited by 380
  2. 2017FeUdal Networks for Hierarchical Reinforcement Learningcited by 328
  3. 2019Learning Latent Plans from Playcited by 310
  4. 2023Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMCcited by 216
  5. 2017Meta Learning Shared Hierarchiescited by 93
  6. 2015Deep Reinforcement Learning in Parameterized Action Spacecited by 65
  7. 2021Accelerating Robotic Reinforcement Learning via Parameterized Action Primitivescited by 63
  8. 2024Diffusion Models, Image Super-Resolution And Everything: A Surveycited by 63
  9. 2015Reinforcement Learning with Parameterized Actionscited by 61
  10. 2024Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrationscited by 51
  11. 2020Multimodal Deep Generative Models for Trajectory Prediction: A Conditional Variational Autoencoder Approachcited by 47
  12. 2025Much Ado About Noising: Dispelling the Myths of Generative Robotic Controlcited by 35
  13. 2023Unsupervised Discovery of Semantic Latent Directions in Diffusion Modelscited by 28
  14. 2024Isometric Representation Learning for Disentangled Latent Space of Diffusion Modelscited by 22
  15. 2024PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Controlcited by 21
  16. 2023Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihoodcited by 19
  17. 2025Semantics Lead the Way: Harmonizing Semantic and Texture Modeling with Asynchronous Latent Diffusioncited by 16
  18. 2022Meta-Learning Parameterized Skillscited by 7
  19. 2024Model-based Reinforcement Learning for Parameterized Action Spacescited by 7
  20. 2025Learning Intractable Multimodal Policies with Reparameterization and Diversity Regularizationcited by 3
  21. 2025PROMPTMINER: Black-Box Prompt Stealing against Text-to-Image Generative Models via Reinforcement Learning and Fuzz Optimizationcited by 2
  22. 2025Learning Parameterized Skills from Demonstrationscited by 1

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  2. 2026Beyond Imitation: Reinforcement Learning Fine-Tuning for Adaptive Diffusion Navigation Policies
  3. 2026Guided Discovery of New Behaviors using Diffusion Policies
  4. 2026Immiscible Diffusion Policy: Preserving Multimodal Robot Actions through Label-Free Noise Assignment
  5. 2025KDPE: A Kernel Density Estimation Strategy for Diffusion Policy Trajectory Selection
  6. 2024Diffusion Policy Policy Optimization
  7. 2024One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation
  8. 2025Flexible Multitask Learning with Factorized Diffusion Policy