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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 2 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 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:43:57.083347Z

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:cddf217a3762db8664a165dd5dc15079f1921b6a1787e424fecc05ef232a1b26

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:d3fd597786ab3b3d99f5cb77ebd5dced18819c03dc9493a413184e4fa6a100a5

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 2026-08-08T06:32:00.761636+00:00.

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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=sha256:4e306e9e0eb5f57ab8b8f1df9cf0eb04e663f98826b1757cb5c7f06c7fd23b18

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:a24ef9b6d4c07caf9ef2f5977ef0f7408bfb537c371a878a04bc76918236e761

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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source=pdf_text observed=2026-08-08T12:53:00.132958Z digest=sha256:4472c833883892c7c8a3ad514ca2a5bc5968c672389b85ad89a216b82461a3fa

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=sha256:1387979bd39c1b15f1ac7bf2227b8daf79a1e2e80ab1374e1dadc50cace8aa18

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=sha256:2dd86fd8db9e973e2d98361cf3c6282e6ec815c95400984bfd7e74112a28728b

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=sha256:90e1e9b7ed116f702d215e5d4e9f82e6768ff93ddfeaac07942977810c155521

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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local_arxiv, observed 2026-08-08T12:53:01.096940Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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:d142cb3bbdb8c477bcd38f14a3f9bd9ca738920417d43464497159b0078e48ff

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:ccb2a98bb0f07d33cad04829b833544cdcece3b77318a76fa4a855c6ef60b0b2

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=sha256:146302f242dab2a844f3fcad58406caa8d41b7bce622a7473a42a95e1831a7a8

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:da388ea4e2812f1e25def83bae7b8886d779037b12e5960e8dad64b27978c308

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=sha256:2f0eb03b1ef26bd00f35ae561cafd1fc3c7bdc7f47e04cfa1e979aff7724ab5b

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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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:a3c92fa766c33a08c392a5ea565a020dee56746d5ddd73bc69b65c598d338942

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=sha256:6c1ef8a68b81fe29d0636d1e1ce7236b53034faacfc357a52f6b008dc5898486

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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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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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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verified fuzzy
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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

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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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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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 2026-08-08T06:32:00.761636+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=sha256:9b0a59d9df4d221a897b14cbf0d280b1f8452822be0f74ac99280757005189af

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T12:53:00.486119Z digest=sha256:2fa95ede52688c60e49a87767e5a65a1c6e59152438b58bbe5d602a63be2fbd3

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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verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T12:53:00.490581Z digest=sha256:f74909ce2423f9221610f2e473c082f45447fc7d3b9e3bb5008d9126620cb9b7

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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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T12:53:00.499136Z digest=sha256:146a622079508f24442d4a85ba89677757377b86b1b4a8ee05f52282596e7f85

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T12:53:00.504407Z digest=sha256:39acc6035867b376a865efd09599725024920d3ceaf068aac84b3d73f9304c1e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T12:53:00.494915Z digest=sha256:e8f8dbda4d26f3f29f3600374cb496bcc5b888a337a989318c46e21ce7863109

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=sha256:28885ac2074cabe0fbee91531fe450f0dcab2082f142e16cd24a4ace0c615986

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=sha256:3d1780608da85f4ffefdd7b2c031709d7b449724894c9a3f9287e1b0c702d6f0

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=sha256:8f8cbb31b47f5c052e280c14f0d8c392cfd18ae7d85f63c2cfa46831cb13f4ee

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=sha256:559aa6a3f31629454f91450071acf5915073d0c5b9a3cb1325e449b9f990c466

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=sha256:55867cd33d4e5a7c9552d58d987eafd2eb14014aad88ee65853b4d0fcbb947bd

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T12:53:00.508863Z digest=sha256:ed061246fcdcaa3b7bd91a8f9985efce6f85b4a82236c4295bad333ac53fd142

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:bb0fbacf5755ccfcd32ac395c46b28d5bbb0c450c1190e5541847861da012c88

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

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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:ea922f4765bd28452633739e0475ada04152d053858591e13e761fcb96cb5e52

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:cad1e9118cf9a1c3ad33ceb5e76fa0c6ecc9cabe39d748bf419353f835622c7a

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:b9c98c437682be188136630afa2b5a5fc6a6bdd25736a4698be29db714f59764

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=sha256:69fc09ed86d6bb72c399cb93f4f8bccc63fa66dcd06a462b8cecead8327a2138

Pith citing papers

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

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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=sha256:52727ff2135f24a748e0fbe4f6011b373d079aa4b99276dd8e906d7029b7581f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T15:20:52.980868Z digest=sha256:3aa8a5e10dee73a93a2990cd63faef11ffcf0b314fcf0049e4d6665414999a80