Paper Citation Record · LEDGER

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation

As of 16 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2411.14913.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.14913 v2

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:48:31.145133Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation febaaf23-7bc2-4db0-aaa7-4f39263a23d6 · outbound

This paper cites More than a million ways to be pushed. a high-fidelity experimental dataset of planar pushing,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation More than a million ways to be pushed. a high-fidelity experimental dataset of planar pushing,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.650628Z

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Observation 2e987559-d8d3-42c6-977b-3681fb0bbda7 · outbound

This paper cites Universal manipulation policy network for articulated objects,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Universal manipulation policy network for articulated objects,

Reference 2

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Observation 1a75905d-b5ac-42fa-ba83-0edffe4ea4c6 · outbound

This paper cites Contact mode guided motion planning for quasidynamic dexterous manipulation in 3d,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Contact mode guided motion planning for quasidynamic dexterous manipulation in 3d,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.630088Z

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Observation 479c545a-6014-4ddd-b08b-c9646d8193fd · outbound

This paper cites Robust execution of contact-rich motion plans by hybrid force-velocity control,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Robust execution of contact-rich motion plans by hybrid force-velocity control,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.614794Z

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Observation c53d2d1a-604b-47a9-ace7-ebac2fa809b9 · outbound

This paper cites Where2act: From pixels to actions for articulated 3d objects,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Where2act: From pixels to actions for articulated 3d objects,

Reference 5

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Observation cbeb2135-84d4-49b1-a847-2fa387cd788a · outbound

This paper cites A hybrid ap- proach for learning to shift and grasp with elaborate motion primitives,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation A hybrid ap- proach for learning to shift and grasp with elaborate motion primitives,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.514804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1d942933-55b9-4e51-961b-083d0e64ef95 · outbound

This paper cites HACMan: Learning hybrid actor-critic maps for 6d non-prehensile manipulation,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation HACMan: Learning hybrid actor-critic maps for 6d non-prehensile manipulation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.427188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3338448e-d685-4d7c-b588-a4e3a8586a9a · outbound

This paper cites Neural probabilistic motor primitives for humanoid control,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Neural probabilistic motor primitives for humanoid control,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.411626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cfc29a3f-d8d7-4374-ae24-1fca99e592b4 · outbound

This paper cites One solution is not all you need: Few-shot extrapolation via structured maxent rl,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation One solution is not all you need: Few-shot extrapolation via structured maxent rl,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.391541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 979267e3-f894-4fce-ae47-5855016d8858 · outbound

This paper cites Towards diverse behaviors: A benchmark for imitation learning with human demonstrations,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Towards diverse behaviors: A benchmark for imitation learning with human demonstrations,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.217674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8bd8e382-fd56-4845-9821-0cf9cf098f34 · outbound

This paper cites Generative modeling by estimating gradients of the data distribution,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Generative modeling by estimating gradients of the data distribution,

Reference 11

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Source-reported events for the cited work

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Observation 82698cde-04d1-4b2e-9295-6ab8f6afda8f · outbound

This paper cites Denoising diffusion probabilistic models,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Denoising diffusion probabilistic models,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.192466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c804a0d1-1ca5-4d03-b7c1-24eca2324a76 · outbound

This paper cites Consistency models as a rich and efficient policy class for reinforcement learning,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Consistency models as a rich and efficient policy class for reinforcement learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.178538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4132dd47-ce97-4ada-ae68-ec39528e956c · outbound

This paper cites Diffusion Policy: Visuomotor Policy Learning via Action Diffusion.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Reference 14

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Source-reported events for the cited work

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Observation 3cb50867-76c9-4a8d-9b78-b660fce80f5a · outbound

This paper cites Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,

Reference 15

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Source-reported events for the cited work

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Observation f3e76ecb-0486-48e8-a388-876af8021b81 · outbound

This paper cites Diffusion policies as an expres- sive policy class for offline reinforcement learning,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Diffusion policies as an expres- sive policy class for offline reinforcement learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.086460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7db96815-8116-4981-a547-b4c5667593c6 · outbound

This paper cites IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T14:48:30.456981Z

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Observation fb1e5365-808a-4aed-80b5-93622854b0aa · outbound

This paper cites Contrastive energy prediction for exact energy-guided diffusion sampling in offline rein- forcement learning,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Contrastive energy prediction for exact energy-guided diffusion sampling in offline rein- forcement learning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.022523Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c1d14f4e-e628-450f-9fdf-8f22efdf5685 · outbound

This paper cites Reasoning with latent diffusion in offline reinforcement learning,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Reasoning with latent diffusion in offline reinforcement learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:32.003866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3f20cc24-feda-4eaa-8275-0f7a0a07c414 · outbound

This paper cites Learning multimodal behaviors from scratch with diffusion policy gra- dient,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Learning multimodal behaviors from scratch with diffusion policy gra- dient,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:31.986176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7c4b0b4d-dc00-4779-8421-0aa0d2e0f4bf · outbound

This paper cites Goal conditioned imitation learning using score-based diffusion policies,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Goal conditioned imitation learning using score-based diffusion policies,

Reference 21

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Source-reported events for the cited work

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Observation 04668f23-4699-45d8-a425-c681d4c0efea · outbound

This paper cites Imitating Human Behaviour with Diffusion Models.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Imitating Human Behaviour with Diffusion Models

Reference 22

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Observation 97b68a1f-13a8-4b39-a9c3-22b4e0ef2ba1 · outbound

This paper cites Offline reinforcement learning via high-fidelity generative behavior modeling,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Offline reinforcement learning via high-fidelity generative behavior modeling,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:31.831815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2a066b47-4a55-4a5d-a829-8387ae8fe6ab · outbound

This paper cites DiffCPS: Diffusion Model based Constrained Policy Search for Offline Reinforcement Learning.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation DiffCPS: Diffusion Model based Constrained Policy Search for Offline Reinforcement Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T14:48:30.566974Z

Source-reported events for the cited work

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Observation 12d4195b-1f5e-4283-afa2-0f415ee5c68d · outbound

This paper cites Reinforcement learning by reward-weighted regression for operational space control,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Reinforcement learning by reward-weighted regression for operational space control,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:31.817442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b5c01eb9-1942-46df-99ad-84bad7c3c82d · outbound

This paper cites Aligning Text-to-Image Models using Human Feedback.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Aligning Text-to-Image Models using Human Feedback

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T14:48:30.576870Z

Source-reported events for the cited work

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Observation 8b7bf6a0-807f-4f07-9b2a-c3f141ad4e3d · outbound

This paper cites Training diffu- sion models with reinforcement learning,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Training diffu- sion models with reinforcement learning,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:31.775250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6a3811f4-1d56-419b-852a-e2158a0ea7e2 · outbound

This paper cites Feedback efficient online fine-tuning of diffusion models,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Feedback efficient online fine-tuning of diffusion models,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:31.680380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5d8a776e-3d03-4c7d-98f3-7f5eed0ee754 · outbound

This paper cites Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T14:48:30.702335Z

Source-reported events for the cited work

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Observation 07e6a49b-df04-46df-a177-0ec39454bb38 · outbound

This paper cites Learning a Diffusion Model Policy from Rewards via Q-Score Matching.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Learning a Diffusion Model Policy from Rewards via Q-Score Matching

Reference 30

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Source-reported events for the cited work

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Observation d133409f-5e61-4eb1-b9c7-7cbc44aa5dc9 · outbound

This paper cites Learning to grasp the ungraspable with emergent extrinsic dexterity,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Learning to grasp the ungraspable with emergent extrinsic dexterity,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:31.633781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ef4e8979-893b-4e21-9e65-cac4c88f15ad · outbound

This paper cites HACMan++: Spatially-Grounded Motion Primitives for Manipulation,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation HACMan++: Spatially-Grounded Motion Primitives for Manipulation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:31.618674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 029051f9-eaa8-4283-bd00-b022b9f11dd1 · outbound

This paper cites Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects

Reference 33

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Source-reported events for the cited work

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Observation 97c47ffc-57ad-41e6-a856-8b8872294587 · outbound

This paper cites Prodmp: A unified perspective on dynamic and probabilistic movement primitives,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Prodmp: A unified perspective on dynamic and probabilistic movement primitives,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:31.603752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a5800fa0-bde8-4854-82da-8d05ba552610 · outbound

This paper cites an unresolved cited work.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Unresolved cited work

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T14:48:30.884271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27e20965-b422-4714-a147-4d42b4dfab8b · outbound

This paper cites Addressing function approxi- mation error in actor-critic methods,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Addressing function approxi- mation error in actor-critic methods,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T14:48:30.900665Z

Source-reported events for the cited work

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Observation 087c788b-56b8-4e55-aefc-36b0c2131136 · outbound

This paper cites Consistency models,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Consistency models,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T14:48:30.907379Z

Source-reported events for the cited work

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Observation ad867a0e-e135-418b-a7f4-ef48bca2e324 · outbound

This paper cites Efficient diffusion policies for offline reinforcement learning,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Efficient diffusion policies for offline reinforcement learning,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:31.468490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bec46b24-0ecb-46ad-afc0-e6dd48881143 · outbound

This paper cites A minimalist approach to offline reinforce- ment learning,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation A minimalist approach to offline reinforce- ment learning,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T14:48:30.916306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56f2f064-2e36-4252-ba89-aead5995fa7c · outbound

This paper cites Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T14:48:30.997318Z

Source-reported events for the cited work

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Observation 85d899b7-b03c-40dd-b295-b59a4411a9ba · outbound

This paper cites robosuite: A Modular Simulation Framework and Benchmark for Robot Learning.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation robosuite: A Modular Simulation Framework and Benchmark for Robot Learning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T14:48:31.095992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73e5f864-71e1-40bd-a30f-532ab89c1b59 · outbound

This paper cites Mujoco: A physics engine for model- based control,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Mujoco: A physics engine for model- based control,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T14:48:31.127842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d671c6fe-2f47-4ef7-b420-2b808b940341 · outbound

This paper cites Deep reinforcement learning at the edge of the statistical precipice,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation Deep reinforcement learning at the edge of the statistical precipice,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:31.382002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 17f99b32-432b-42a4-95d7-2c3c60adb074 · outbound

This paper cites CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Ob- jects,.

Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL: Application to Non-Prehensile Manipulation CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Ob- jects,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:48:31.343831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.