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Paper Citation Record · LEDGER

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL

As of 19 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2506.03154.

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

pith.paper-citation-record.v1
2506.03154 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:15:39.462514Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

23 of 23 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ef70bdb-93b0-43a1-af9f-31d44d42b154 · outbound

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

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Reference 2

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no resolver link, observed 2026-08-15T20:15:39.375185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:15:39.375185Z digest=sha256:6b8f6157673ffeb287a5c28468c2436f0c52337a94d0a10f8f24e95d630810c5

Observation fb73ec53-3000-4dbd-903b-e98d5f786692 · outbound

This paper cites Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

Reference 3

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no resolver link, observed 2026-08-15T20:15:39.379057Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:15:39.379057Z digest=sha256:11d21569724b2a564311d9c68db7e4cc634a497b2fe6447cdc23bd6a8f473850

Observation c26c760c-32a8-41f2-accd-2f6470b63a2b · outbound

This paper cites Diffusion Policies creating a Trust Region for Offline Reinforcement Learning.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Diffusion Policies creating a Trust Region for Offline Reinforcement Learning

Reference 5

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source=arxiv_source observed=2026-08-15T20:15:39.387710Z digest=sha256:e2622da25d846aad26011d04369c6e62c959976d3d3ff26a056c3f80fa2d5579

Observation 536a947b-cb66-487a-b9f9-028b5593a9be · outbound

This paper cites Classifier-Free Diffusion Guidance.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Classifier-Free Diffusion Guidance

Reference 6

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:15:39.392500Z digest=sha256:0c6041d019c5ce0d6b03b3b02957818600eb48ae83ff5fdbe21c399406f21f7b

Observation 0972ae88-e3aa-476f-9e1c-a4397bb18c71 · outbound

This paper cites Refining generative process with discriminator guidance in score-based diffusion models.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Refining generative process with discriminator guidance in score-based diffusion models

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-15T20:15:39.716090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T20:15:39.396813Z digest=sha256:3671203d349a4cde132274b997fd4011f21e830041669d4ca7135fa6508e558e

Observation 0a429f42-18a1-4a6d-a09b-891fba995c29 · outbound

This paper cites Towards Controllable Diffusion Models via Reward-Guided Exploration.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Towards Controllable Diffusion Models via Reward-Guided Exploration

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:15:39.401045Z digest=sha256:00f9d13b7a35c2db86f4b7fa65ef6fd481ae00e8ac3286f189c6c584e3029cff

Observation 5ae8b8d3-b281-4c72-aeae-26e79f508cec · outbound

This paper cites Inference-time alignment in diffusion models with reward-guided generation: Tutorial and review, 2025.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Inference-time alignment in diffusion models with reward-guided generation: Tutorial and review, 2025

Reference 9

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source=arxiv_source observed=2026-08-15T20:15:39.405409Z digest=sha256:fd0b7db1e12e516694ee2c3be0803e017c9fa9a521abddc8acb1ff697688fee9

Observation ba03d29b-f8fb-4753-9e03-04f17c18c80e · outbound

This paper cites Double q-learning.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Double q-learning

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-15T20:15:39.699771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T20:15:39.408718Z digest=sha256:5f98f9dec294670c4fda95e30e8d4f56cef31af3a615c943c4280bb09f8ea1ad

Observation 62fb2d73-d556-40b3-a542-5481e09d3f8b · outbound

This paper cites Adding conditional control to diffusion models with reinforcement learning.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Adding conditional control to diffusion models with reinforcement learning

Reference 11

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raw_fallback, observed 2026-08-15T20:15:39.690294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T20:15:39.413280Z digest=sha256:7890f640f77001e27cd67e18f8900a65eeb296bfb2a88a527e211d9dc3d508de

Observation b2654d28-3fd0-48c6-ad5a-1f142bc1f4f9 · outbound

This paper cites Planning with Diffusion for Flexible Behavior Synthesis.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Planning with Diffusion for Flexible Behavior Synthesis

Reference 12

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source=arxiv_source observed=2026-08-15T20:15:39.416567Z digest=sha256:55cac81fef05d505e5ecb8268e8320e00847c8bdd5f1071ea2c1ceef557dab5d

Observation 56a1dd76-7d46-4872-8f67-d9bd97714ae8 · outbound

This paper cites Coupling OpenFOAM(R) with BoSSS, a discontinuous Galerkin solver written in C#.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Coupling OpenFOAM(R) with BoSSS, a discontinuous Galerkin solver written in C#

Reference 13

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local_arxiv, observed 2026-08-15T20:15:39.583656Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T20:15:39.419607Z digest=sha256:04d654563e60469aca8110461708f95e2421ac2e44a95de3e30e146e78e738bb

Observation 0e873813-49eb-4484-be36-b20b2e720fa0 · outbound

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

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies

Reference 14

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no resolver link, observed 2026-08-15T20:15:39.423408Z

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source=arxiv_source observed=2026-08-15T20:15:39.423408Z digest=sha256:911783a3d0a5132c00b7887f6b3f7157873db5d12e58f050a3d1a488253673ee

Observation c01e1076-39e8-40df-8526-f40b2cf432d8 · outbound

This paper cites Benchmarking Batch Deep Reinforcement Learning Algorithms.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Benchmarking Batch Deep Reinforcement Learning Algorithms

Reference 15

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:15:39.426563Z digest=sha256:8632693d2dbf9faf5fd63cd0753ffe8b9f19b130af0235ce58318f07156d2f6a

Observation 4a32efde-3170-4f7a-91ec-69a8942e7748 · outbound

This paper cites D4RL: Datasets for Deep Data-Driven Reinforcement Learning.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Reference 16

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source=arxiv_source observed=2026-08-15T20:15:39.430011Z digest=sha256:d82e855a82617864381d6cfdbab5308c5a17851e02ed9c2cf195eda3f0b7ce9d

Observation 28d31214-43cf-4de8-aca3-7f4180b6221e · outbound

This paper cites Site-selective preparation and multi-state readout of molecules in optical tweezers.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Site-selective preparation and multi-state readout of molecules in optical tweezers

Reference 17

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local_arxiv, observed 2026-08-15T20:15:39.552789Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T20:15:39.433321Z digest=sha256:3bacc5ffe9b29adb09284ee0fe07c1fbdf730135362c26b445064b17995f8db2

Observation ff820e05-aa39-44ec-b075-2bf4ac505742 · outbound

This paper cites Gymnasium: A standard api for reinforcement learning environments.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Gymnasium: A standard api for reinforcement learning environments

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-15T20:15:39.680296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T20:15:39.436636Z digest=sha256:e2cdd96e53410f19d548dea126d1bf1b3b17b904df3facd6c02b50d7dbac55a3

Observation adc3f72f-07c4-41fb-b474-579045f9875f · outbound

This paper cites D4rl: Datasets for deep data-driven reinforcement learning.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL D4rl: Datasets for deep data-driven reinforcement learning

Reference 19

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T20:15:39.439894Z digest=sha256:d27b8681fedbc93ebeac1e468c793dcc7e3472d93ce99954e6736a329798fee2

Observation 922e1ffe-8cbb-48e2-afff-d26c04669034 · outbound

This paper cites Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning

Reference 20

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source=arxiv_source observed=2026-08-15T20:15:39.443488Z digest=sha256:9e49401bed07168dd439710aa27fd929bfb61904c440d52bed5f1fcb1335e660

Observation b9911756-2e4f-4497-9055-90d03531684f · outbound

This paper cites Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning

Reference 21

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source=arxiv_source observed=2026-08-15T20:15:39.446957Z digest=sha256:f4761ac6fa838e19db376cb470d492f3e0da9b382622ba33c632716acece148e

Observation 04eb5fc3-77b7-4a87-b6f4-ae5d74d68430 · outbound

This paper cites Hydrodynamic modeling of heavy-ion collisions.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Hydrodynamic modeling of heavy-ion collisions

Reference 22

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metadata mismatch
local_arxiv, observed 2026-08-15T20:15:39.519408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T20:15:39.450422Z digest=sha256:5158204a92b22494c460e97557ef6deaae1fc03aac785afd76e7787580cad217

Observation b421836c-31ed-4707-9eb1-bf5f4f126777 · outbound

This paper cites Layer-dependent spin-orbit torques generated by the centrosymmetric transition metal dichalcogenide $\beta$-MoTe$_2$.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Layer-dependent spin-orbit torques generated by the centrosymmetric transition metal dichalcogenide $\beta$-MoTe$_2$

Reference 23

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source=arxiv_source observed=2026-08-15T20:15:39.453826Z digest=sha256:47269896c9f2c564b74f88a9bdc313ee0a0c0a73fbe872e599ef5019db774f04

Observation aee7e07a-520c-40e3-bae5-986f5bf91458 · outbound

This paper cites Analysis of Classifier-Free Guidance Weight Schedulers.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Analysis of Classifier-Free Guidance Weight Schedulers

Reference 24

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source=arxiv_source observed=2026-08-15T20:15:39.458119Z digest=sha256:856f16521ab7bf23e2d907c75a5f65fd11d23aed6c3335a6d7d11fe949e6c620

Observation 2e0df34f-f2ef-4968-8a14-52c70d671a87 · outbound

This paper cites Plug and play, model-based reinforcement learning, 2021.

Modular Diffusion Policy Training: Decoupling and Recombining Guidance and Diffusion for Offline RL Plug and play, model-based reinforcement learning, 2021

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-15T20:15:39.660503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T20:15:39.462514Z digest=sha256:3f3b1dac3f4e6b365742394dc0314a42849cd4965825a5e7cf7725764475458a

Pith citing papers

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