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Paper Citation Record · LEDGER

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms

As of 18 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 3 inbound Pith citation observations for arXiv:2502.07849.

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

pith.paper-citation-record.v1
2502.07849 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:53:00.508863Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T22:20:18.204136Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:26:18.121448Z

Reference resolution

49 of 49 outbound references displayed

  • verified exact2
  • verified fuzzy7
  • unresolved37
  • parse uncertain0
  • malformed identifier3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ae3aa185-7cfc-401c-92ab-a0c2f31b432a · outbound

This paper cites Memorization and Generalization in Generative Diffusion under the Manifold Hypothesis.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Memorization and Generalization in Generative Diffusion under the Manifold Hypothesis

Reference 1

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Observation 48aa3789-23a3-4a07-aab8-3582cda5ead5 · outbound

This paper cites Consistency-diversity-realism Pareto fronts of conditional image generative models.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Consistency-diversity-realism Pareto fronts of conditional image generative models

Reference 4

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source=pdf_text observed=2026-08-08T12:52:59.945665Z digest=sha256:3124da0bb45d1c8239bed360d7709eea870fc7c8619971a62481bf21b0f4ed2e

Observation 0bb86078-86b8-425e-b18e-b32df05f590a · outbound

This paper cites An Expectation-Maximization Algorithm for Training Clean Diffusion Models from Corrupted Observations.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms An Expectation-Maximization Algorithm for Training Clean Diffusion Models from Corrupted Observations

Reference 6

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source=pdf_text observed=2026-08-08T12:53:00.038675Z digest=sha256:6ef210dcb7f610744f21f220a11cd390cebe4a8040af115a6793805c0bb1b731

Observation b3e8ff13-0276-472f-8467-77c72127f8a3 · outbound

This paper cites Generative diffusion in very large dimensions.Journal of Statistical Mechanics: Theory and Experiment, 2023(9):093402,.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Generative diffusion in very large dimensions.Journal of Statistical Mechanics: Theory and Experiment, 2023(9):093402,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-08T12:53:00.114060Z digest=sha256:3fc892ab469e393a54d45be9293de11f8ab3e1b15a06a17d54a733b4aa426838

Observation 7036cf6e-253b-48f1-8536-329fb6f1653b · outbound

This paper cites Dynamical Regimes of Diffusion Models.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Dynamical Regimes of Diffusion Models

Reference 8

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source=pdf_text observed=2026-08-08T12:53:00.119207Z digest=sha256:778e9c39e64c87a201826a961d82760987840a93c44ce7a2f0b878c27be62611

Observation a1a20e26-0fd3-4a02-9321-aa3f3d24f142 · outbound

This paper cites Classifier-Free Guidance is a Predictor-Corrector.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Classifier-Free Guidance is a Predictor-Corrector

Reference 9

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source=pdf_text observed=2026-08-08T12:53:00.123738Z digest=sha256:79309ffc099804f293b7fb6b8c33d8dadb6bd350c64372156bddd1b684e285e3

Observation b11f1e51-2f73-49ba-9511-07d658fdfcdb · outbound

This paper cites an unresolved cited work.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Unresolved cited work

Reference 10

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Observation ec8faef8-3ad7-4446-8c3f-b873348467e1 · outbound

This paper cites CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models

Reference 11

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Observation cc9fb163-d20f-4cfa-b356-210fa11c8f99 · outbound

This paper cites Analysis of learning a flow-based generative model from limited sample complexity.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Analysis of learning a flow-based generative model from limited sample complexity

Reference 12

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source=pdf_text observed=2026-08-08T12:53:00.137222Z digest=sha256:bc900fc27f1437542f4dfcb669dd710243526002193c4d46eaed37d4b387234b

Observation c9c83f39-40d3-402f-9046-23d20c7c431f · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Imagenet: A large-scale hierarchical image database

Reference 13

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source=pdf_text observed=2026-08-08T12:53:00.141132Z digest=sha256:e9d56fbcefe44bac660c26ec6f9090ca88c5e967fda970b9e5fe6d8f3121b8b8

Observation 18cec129-d465-4717-9e50-9c97508fdd09 · outbound

This paper cites Analysis of diffusion models for manifold data.arXiv preprint arXiv:2502.04339,.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Analysis of diffusion models for manifold data.arXiv preprint arXiv:2502.04339,

Reference 14

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source=pdf_text observed=2026-08-08T12:53:00.145935Z digest=sha256:a20e7f61371e4897bd800b6fee548eef4117d56724379cc953e6c33df98d48f5

Observation 57922fe6-88bc-4121-ae5b-45ac16d64927 · outbound

This paper cites EvalGIM: A Library for Evaluating Generative Image Models.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms EvalGIM: A Library for Evaluating Generative Image Models

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8d64d8be-99b9-4e1d-935d-3b15138597d2 · outbound

This paper cites Guiding a Diffusion Model with a Bad Version of Itself.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Guiding a Diffusion Model with a Bad Version of Itself

Reference 18

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Observation b1163e9b-baa9-4a81-82ee-fb1ae0d76e42 · outbound

This paper cites Critical windows: non-asymptotic theory for feature emergence in diffusion models.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Critical windows: non-asymptotic theory for feature emergence in diffusion models

Reference 19

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source=pdf_text observed=2026-08-08T12:53:00.168063Z digest=sha256:f4012890ee9977ae2b943a469d792bd313aca6ffc501d4990626ea9b82777e59

Observation 81f5e5ca-2bb3-4585-89e7-ff12e4f4b1a6 · outbound

This paper cites Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective

Reference 20

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source=pdf_text observed=2026-08-08T12:53:00.172338Z digest=sha256:826abc518c5044a39681242bfcfffaef99519fdb058026cc3f959df627d49225

Observation 61862e7e-1a15-47ec-af80-18c1c5bbad04 · outbound

This paper cites Microsoft coco: Common objects in context.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Microsoft coco: Common objects in context

Reference 21

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source=pdf_text observed=2026-08-08T12:53:00.176366Z digest=sha256:e7fe27627fab8ffb2e03c4961b391c0ecb6996c1712e623ce6f343593dbfe8e9

Observation 4d2b84ab-06d4-453d-ac26-b83eab6c351b · outbound

This paper cites Flow Matching Guide and Code.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Flow Matching Guide and Code

Reference 23

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source=pdf_text observed=2026-08-08T12:53:00.185336Z digest=sha256:bba3c64ae0ea01a749777a225ae9e3b42738cbbfa0ca8471ccce2824819ab02c

Observation f23ffc8d-2655-4a46-b1a7-737153b2e25a · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 24

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Observation 59c88683-697c-423a-ab9d-291cc64bbe84 · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 25

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Observation 11fcc5eb-7110-4a2f-8386-f124ee12d99a · outbound

This paper cites CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling

Reference 26

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source=pdf_text observed=2026-08-08T12:53:00.307591Z digest=sha256:ec1574e0dfb5a1786740a3854236b314fadc7d0e9fb8d1bb7de77634b8ebade6

Observation 2dbf9f21-71dd-415f-8bd9-29281d32c206 · outbound

This paper cites Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion

Reference 29

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source=pdf_text observed=2026-08-08T12:53:00.409706Z digest=sha256:9d6a5eddc8267501807e5b8c1f9903fa8b926ee24c9c0432cb6a5ce7263a11ef

Observation 7b051576-f874-48c8-b9d7-5c06dfe42a79 · outbound

This paper cites Theoretical Insights for Diffusion Guidance: A Case Study for Gaussian Mixture Models.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Theoretical Insights for Diffusion Guidance: A Case Study for Gaussian Mixture Models

Reference 31

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source=pdf_text observed=2026-08-08T12:53:00.421689Z digest=sha256:267a94a390f610136566c90b3b6ba90690593842c817c6bea6c63301ccadd5e0

Observation 6aafdc05-5c15-4d03-8af0-2523bf2552ff · outbound

This paper cites Rectified diffusion guidance for conditional generation.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Rectified diffusion guidance for conditional generation

Reference 32

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source=pdf_text observed=2026-08-08T12:53:00.427497Z digest=sha256:8250f53c70d090c194b51e24248c850114d8b6d41dd8d405a46f493d9a33f06f

Observation ac423554-a29f-4c4c-96ed-6756b9098bd3 · outbound

This paper cites Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks

Reference 33

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source=pdf_text observed=2026-08-08T12:53:00.432294Z digest=sha256:fc6250fecf641c5af36277704a3635932ee676a522cce0bca0247ea265cf06ec

Observation d6895f07-25a7-48c6-82e1-2c5a609fa702 · outbound

This paper cites Nonequilbrium physics of generative diffusion models.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Nonequilbrium physics of generative diffusion models

Reference 34

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b9b12a3a-5e0d-415a-aa99-538d6719c49f · outbound

This paper cites Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance Scale.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance Scale

Reference 35

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Observation aefd932c-fbc2-421c-96a6-adf9405121d0 · outbound

This paper cites an unresolved cited work.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Unresolved cited work

Reference 36

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8e5f0a3a-366c-4dd8-b5d3-060539fe18fb · outbound

This paper cites transverse.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms transverse

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6b5f0070-c291-49cd-8081-d40914af8477 · outbound

This paper cites transverse.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms transverse

Reference 38

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raw_fallback, observed 2026-08-08T12:53:01.592193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 479dd196-1e90-4fcc-b27a-a14aad113437 · outbound

This paper cites Table 2 Assets used for our work.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Table 2 Assets used for our work

Reference 39

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-08T12:53:00.462469Z digest=sha256:424a7ce4abac347c13dfb7ebe8fcf35ccdbbb9b0f1728c4576a57ef52643716a

Observation 045d483b-f623-40bd-8384-efa9b3e678ed · outbound

This paper cites The last two plots correspond to the actual trajectories projected onto the target mean +⃗ mfor values ofω∈{ 0., 5., 10., 15., 20.}.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms The last two plots correspond to the actual trajectories projected onto the target mean +⃗ mfor values ofω∈{ 0., 5., 10., 15., 20.}

Reference 41

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-08T12:53:00.471584Z digest=sha256:840a3d4fa47e6c153f6a8970a2bfa5d88ba6c93b8518aee80c9f8e86e4f65741

Observation f301b62c-456a-4b24-a6a7-63e453b52484 · outbound

This paper cites In Figure 10, we use DiT/XL-2 model trained on 2, 500 and 1000 classes.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms In Figure 10, we use DiT/XL-2 model trained on 2, 500 and 1000 classes

Reference 42

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0fb4fefd-3047-4301-8850-aa1d09a255b2 · outbound

This paper cites an unresolved cited work.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Unresolved cited work

Reference 43

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source=pdf_text observed=2026-08-08T12:53:00.481701Z digest=sha256:591a4b4b865058547cd696fb5cf09b73825e69d919e0a06e70df7bb9741c6fb0

Observation 083e879c-e4c1-47cf-be17-ab39a14e1792 · outbound

This paper cites In Table 4 present additional quantitative evaluations of our method, focusing on diversity and coverage metrics (as described in Hall et al.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms In Table 4 present additional quantitative evaluations of our method, focusing on diversity and coverage metrics (as described in Hall et al

Reference 44

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raw_fallback, observed 2026-08-08T12:53:01.517839Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-08T12:53:00.486119Z digest=sha256:d4b17bbb1c928e8f7b615893465f5a3916c9f77ae196d1ec1cbc8aafcd194990

Observation 76bdad64-480a-42da-a01f-38b57f411698 · outbound

This paper cites As demonstrated in the main manuscript, power-law CFG generally outperforms standard CFG (indicated by arrows in the table).

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms As demonstrated in the main manuscript, power-law CFG generally outperforms standard CFG (indicated by arrows in the table)

Reference 45

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raw_fallback, observed 2026-08-08T12:53:01.504030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-08T12:53:00.490581Z digest=sha256:12de0c7217e7f1386800a63cb1634d06008edfe7604610321626367641dea5ab

Observation 32381ed7-ccdb-435d-a8b7-8c3209eabf54 · outbound

This paper cites steps α ω FID (↓) IS (↑) Precision (↑) Recall (↑) sFID (↓) Stand.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms steps α ω FID (↓) IS (↑) Precision (↑) Recall (↑) sFID (↓) Stand

Reference 47

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malformed identifier
raw_fallback, observed 2026-08-08T12:53:01.478514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-08T12:53:00.499136Z digest=sha256:449ed676237d3a2190028fce23b0de2f09d584ba19c3c2b08b4f8ae1b4b37b7f

Observation bf10e422-4591-4911-aad0-9b75cf8d1e9e · outbound

This paper cites an unresolved cited work.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Unresolved cited work

Reference 48

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unresolved
raw_fallback, observed 2026-08-08T12:53:01.466352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-08T12:53:00.504407Z digest=sha256:38f5cbb1f22a6840553cf73c1b88084eae35abdd1d043ea796e8fe60afdc6042

Observation 4700e18e-93e7-44db-bb04-5be900f98b11 · outbound

This paper cites an unresolved cited work.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Unresolved cited work

Reference 256

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unresolved
raw_fallback, observed 2026-08-08T12:53:01.491269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-08T12:53:00.494915Z digest=sha256:62bafa25962307808447e754da0344a0c025c8228c339a75b229d99f1666cf6e

Observation a8e8276d-c221-44a1-88b5-2f566eb7fbb2 · outbound

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

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Analysis of Classifier-Free Guidance Weight Schedulers

Reference 2009

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unresolved
no resolver link, observed 2026-08-08T12:53:00.415763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:53:00.415763Z digest=sha256:5ed89c26cc6a7b5b98e07c67a94020ed207100acf9f18dcdc52ff154105f6e50

Observation 8bf3df5f-8aca-4a09-a9fb-00608b3fc5b0 · outbound

This paper cites Flow Matching for Generative Modeling.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Flow Matching for Generative Modeling

Reference 2014

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unresolved
no resolver link, observed 2026-08-08T12:53:00.180720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:53:00.180720Z digest=sha256:0c873ae6ffd5593e92c9ebff417445922f57e73c252f9f37f19b3735cc0b173a

Observation 5c2e3f80-775c-46b1-af59-cfe2aa30ae6d · outbound

This paper cites Deep Unsupervised Learning using Nonequilibrium Thermodynamics.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Reference 2015

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unresolved
no resolver link, observed 2026-08-08T12:53:00.389485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:53:00.389485Z digest=sha256:3ccf830b53860ef87bb393bce5031ad90a7794aedfb9cc77b99cd710d696facf

Observation cf8fd088-9dfa-462f-a9a9-f2f4e0e2e897 · outbound

This paper cites A Phase Transition in Diffusion Models Reveals the Hierarchical Nature of Data.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms A Phase Transition in Diffusion Models Reveals the Hierarchical Nature of Data

Reference 2016

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unresolved
no resolver link, observed 2026-08-08T12:53:00.345399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:53:00.345399Z digest=sha256:e4029ac9da6e26a700c49e2b6ecf4d661749092ae53c8f54ebf89dcd5828b9a5

Observation 3c2a5280-f38b-4c95-8193-648f8d465707 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Classifier-Free Diffusion Guidance

Reference 2017

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no resolver link, observed 2026-08-08T12:53:00.154245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:53:00.154245Z digest=sha256:0dc1bfac9701b987a1eb83f79f2888b08c5699fcf3b90797b6a01691711686c8

Observation b1bff04f-95e2-4270-91c0-194a5d4362bc · outbound

This paper cites an unresolved cited work.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Unresolved cited work

Reference 2020

Resolution
unresolved
raw_fallback, observed 2026-08-08T12:53:01.441262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-08T12:53:00.508863Z digest=sha256:abbe669718bcc6d378ccd040ec5e45b45ed9fc95d69ec214701ce2b0b8f50554

Observation 4a758e6c-e951-4105-8938-4711c52d7ea6 · outbound

This paper cites What does guidance do? A fine-grained analysis in a simple setting.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms What does guidance do? A fine-grained analysis in a simple setting

Reference 2021

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unresolved
no resolver link, observed 2026-08-08T12:53:00.128211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:53:00.128211Z digest=sha256:ef28c02b0e42f4367ab45406225151ad7c8fdc385d6d55b986da1fe2e2adba39

Observation 7183bba3-097b-4cb9-a62d-52ba07bb39e2 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Denoising Diffusion Probabilistic Models

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-08T12:53:00.158828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:53:00.158828Z digest=sha256:992c5cef1df5b1497f2ce1fbdcfb29b658f2eacd9371ea65b28d14aec52c9c3d

Observation 4060be92-d7f9-4166-8d3c-ea01e88b666d · outbound

This paper cites Optimizing Noise Schedules of Generative Models in High Dimensionss.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Optimizing Noise Schedules of Generative Models in High Dimensionss

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-08T12:52:59.898242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:52:59.898242Z digest=sha256:1ec908ad2d272d9052a65147bb46fcc542ece7890a7347049569e4d433ea09c5

Observation 3c6fb93c-0c49-4b0f-81ab-7e52dd579c6d · outbound

This paper cites A Very Effective and Simple Diffusion Reconstruction for the Diluted Ising Model.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms A Very Effective and Simple Diffusion Reconstruction for the Diluted Ising Model

Reference 2024

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unresolved
no resolver link, observed 2026-08-08T12:52:59.991419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:52:59.991419Z digest=sha256:f7022fc3771bf9f634776721ba409eb4b6e6be0b1733bebac8a27a043ac0639b

Observation 4151b1df-9ebe-4f38-b01c-0f44a201e622 · outbound

This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.

Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

Reference 2025

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unresolved
no resolver link, observed 2026-08-08T12:52:59.889719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:52:59.889719Z digest=sha256:cf9605d6d1654bf8283398e6feefdd2fefae6ebdf8b5d052dec9b720813afa58

Pith citing papers

Observation abdf9dae-55b2-47a0-adf4-611d7d6323ea · inbound

REG: Rectified Gradient Guidance for Conditional Diffusion Models cites this paper.

REG: Rectified Gradient Guidance for Conditional Diffusion Models Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-09T22:20:18.204136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T22:20:18.204136Z digest=sha256:4d0c341a99680107895a49a1de05c6daf2ec3d77947b7a93f1df32b75c2354f4

Observation ec51dfe9-27da-4004-b7e9-4c054eee6d94 · inbound

Conditional Diffusion Models with Classifier-Free Gibbs-like Guidance cites this paper.

Conditional Diffusion Models with Classifier-Free Gibbs-like Guidance Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T13:43:57.083347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:43:57.083347Z digest=sha256:090a7e1746c8937c91b3ff2e0bdae6f5f51063f5f245325825c4b36110f6f442

Observation 9a2d6b65-a011-4728-97fe-ddcce2e93a0f · inbound

Are we really tilting? The mechanics of reward guidance in flow and diffusion models cites this paper.

Are we really tilting? The mechanics of reward guidance in flow and diffusion models Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-01T22:26:18.122960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-28T15:20:52.980868Z digest=sha256:bbaf04471613464f307b0025b9e6b2772948dea7281592a35202018be6b4eb5e