Paper Citation Record · LEDGER

Certified Guidance for Planning with Deep Generative Models

As of 11 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2501.12815.

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

pith.paper-citation-record.v1
2501.12815 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:51:20.164534Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

42 of 42 outbound references displayed

verified exact0
verified fuzzy7
unresolved35
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

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Outbound references

Observation 3cd74f3c-519a-4369-a90f-3c7a222ac61d · outbound

This paper cites Is Conditional Generative Modeling all you need for Decision-Making?.

Certified Guidance for Planning with Deep Generative Models Is Conditional Generative Modeling all you need for Decision-Making?

Reference 1

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Unavailable: canonical work link unavailable.

Observation 3da62918-58a8-456e-a068-1baec2c2538f · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.566487Z

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Observation 2d5e542e-5813-4f3c-92a0-f621dff4ca15 · outbound

This paper cites Wasserstein GAN.

Certified Guidance for Planning with Deep Generative Models Wasserstein GAN

Reference 3

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Observation 6e6cd1ee-84a6-4eb9-880b-f3b0da9abff3 · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.545223Z

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Observation bfc205fe-ac21-4b88-88bf-37917d6ea760 · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.535254Z

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Observation 5a59a4fc-eab7-4432-8ee4-0924f5c70245 · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.526205Z

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Observation 11ebbd60-38a2-43dd-b881-db99b3cc2cb0 · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.517208Z

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Observation 1cda9fea-5b56-4573-bbc7-1913809ec9d8 · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 8

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Observation 350380a0-6787-407d-9161-97a73af8ef37 · outbound

This paper cites 2016.Deep learning.

Certified Guidance for Planning with Deep Generative Models 2016.Deep learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:51:20.495919Z

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Observation 4e840969-e3eb-412d-b085-100868c86267 · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 10

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Observation 2b19cd1e-ae02-45df-ba36-a9e1b110e33d · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:20.072813Z

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Observation b868528e-4bb4-4a8d-a0e2-c7e8e8559c31 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

Certified Guidance for Planning with Deep Generative Models Denoising Diffusion Probabilistic Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:20.075600Z

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Observation 513aeae1-033b-4120-89ed-cbb8e56ffaea · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.474107Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0670a9b6-bb75-419f-bcd8-1efc76cb2080 · outbound

This paper cites Planning with Diffusion for Flexible Behavior Synthesis.

Certified Guidance for Planning with Deep Generative Models Planning with Diffusion for Flexible Behavior Synthesis

Reference 14

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Observation 782a1072-9190-4362-85cb-6948e7f0530d · outbound

This paper cites Tenenbaum, and Sergey Levine.

Certified Guidance for Planning with Deep Generative Models Tenenbaum, and Sergey Levine

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:51:20.464152Z

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Observation 1dd87400-9b4c-458d-90da-f270b3bad638 · outbound

This paper cites Katz, Anthony L.

Certified Guidance for Planning with Deep Generative Models Katz, Anthony L

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:51:20.454446Z

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Observation eb3de1e2-3052-4a82-891e-21e37ae5bdeb · outbound

This paper cites Kavraki, P.

Certified Guidance for Planning with Deep Generative Models Kavraki, P

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:20.092068Z

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Observation abfef9de-bc39-4328-9c95-1c24f0003b72 · outbound

This paper cites Conformal Off-Policy Prediction for Multi-Agent Systems.

Certified Guidance for Planning with Deep Generative Models Conformal Off-Policy Prediction for Multi-Agent Systems

Reference 18

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Observation 4e5014ce-5e9b-4743-877a-887746ba081e · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.444988Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 41337159-851c-4c38-8ebb-f4896e234754 · outbound

This paper cites On the Variance of the Adaptive Learning Rate and Beyond.

Certified Guidance for Planning with Deep Generative Models On the Variance of the Adaptive Learning Rate and Beyond

Reference 20

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Observation 4d139a0d-5edb-4f25-822e-a535a78c119c · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.435166Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b839486e-7eaa-4966-bd0c-d7d05574f13c · outbound

This paper cites Conditional Generative Adversarial Nets.

Certified Guidance for Planning with Deep Generative Models Conditional Generative Adversarial Nets

Reference 22

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Observation 326440e7-7c48-4678-9e52-bfbfe3dea38c · outbound

This paper cites Improved Denoising Diffusion Probabilistic Models.

Certified Guidance for Planning with Deep Generative Models Improved Denoising Diffusion Probabilistic Models

Reference 23

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Observation d227ac5f-dc94-49e1-8306-5efb7aa8b5db · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.425964Z

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Observation 83ab8a51-3f89-4b68-b850-37243fab850b · outbound

This paper cites Weiss, Niru Maheswaranathan, and Surya Ganguli.

Certified Guidance for Planning with Deep Generative Models Weiss, Niru Maheswaranathan, and Surya Ganguli

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:20.119533Z

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Observation d9dbd236-4a03-4dd8-b657-732170a0db1b · outbound

This paper cites Denoising Diffusion Implicit Models.

Certified Guidance for Planning with Deep Generative Models Denoising Diffusion Implicit Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:20.126572Z

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Observation 0b00cbd7-80e1-4f91-8aeb-0fd760242d63 · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:20.129545Z

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Observation e1a279d2-4f29-460e-86b6-f120e8a75b59 · outbound

This paper cites Generative Modeling by Estimating Gradients of the Data Distribution.

Certified Guidance for Planning with Deep Generative Models Generative Modeling by Estimating Gradients of the Data Distribution

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:20.132263Z

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Observation 4dabc1b8-b286-4b58-8c4e-3333536d869e · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.404595Z

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Observation bbbb9f32-f582-4d81-a012-4fa3a4956ca9 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Certified Guidance for Planning with Deep Generative Models Score-Based Generative Modeling through Stochastic Differential Equations

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:20.138478Z

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Observation 7853089d-ef6c-444d-8022-8a25440ccbd1 · outbound

This paper cites Kochenderfer, and Mac Schwager.

Certified Guidance for Planning with Deep Generative Models Kochenderfer, and Mac Schwager

Reference 31

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8ca70b85-0845-415d-9ad2-c4f731e3af40 · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 32

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Observation c4e66f7a-0b32-471d-bfa9-b5336270e5f4 · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.374912Z

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Observation 5c5e13d0-255c-4fe4-8b2b-b0f5156db8ce · outbound

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Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.365645Z

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Observation a8200ac2-74b2-48ab-93cf-4093b88607ce · outbound

This paper cites an unresolved cited work.

Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 35

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Observation 8c68454d-c01c-4646-b977-1125bff7f2de · outbound

This paper cites SafeDiffuser: Safe Planning with Diffusion Probabilistic Models.

Certified Guidance for Planning with Deep Generative Models SafeDiffuser: Safe Planning with Diffusion Probabilistic Models

Reference 36

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Observation 347d5f30-c891-4a48-b2bb-df12085cb683 · outbound

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Certified Guidance for Planning with Deep Generative Models Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-10T16:51:20.347189Z

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Observation 9f86c2a0-5307-460f-93fb-284d9583e2e8 · outbound

This paper cites This training objective can also be viewed as a weighted combination of denoising score matching used for training score-based generative models [27, 29, 30].

Certified Guidance for Planning with Deep Generative Models This training objective can also be viewed as a weighted combination of denoising score matching used for training score-based generative models [27, 29, 30]

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:51:20.337067Z

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Observation df802d1e-a856-4802-95e6-c8d4bc10f13c · outbound

This paper cites The computational burden and complexity of sampling from a trained DDPM can be reduced by resorting to their implicit formulation [26].

Certified Guidance for Planning with Deep Generative Models The computational burden and complexity of sampling from a trained DDPM can be reduced by resorting to their implicit formulation [26]

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:51:20.325443Z

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Observation 7a73d59c-3963-47a9-95f3-c93c2247fcb2 · outbound

This paper cites Deep Unsupervised Learning using Nonequilibrium Thermodynamics.

Certified Guidance for Planning with Deep Generative Models Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Reference 2015

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Observation cdd94ea8-dd7f-4417-a504-a68c53b75b1b · outbound

This paper cites Journal of Autonomous Agents and Multi-Agent Systems 36, 1 (2022).

Certified Guidance for Planning with Deep Generative Models Journal of Autonomous Agents and Multi-Agent Systems 36, 1 (2022)

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T16:51:20.556301Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d367c507-f34e-42b2-b655-5f53a489adec · outbound

This paper cites DiffuserLite: Towards Real-time Diffusion Planning.

Certified Guidance for Planning with Deep Generative Models DiffuserLite: Towards Real-time Diffusion Planning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T16:51:20.061213Z

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Pith citing papers

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