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Paper Citation Record · LEDGER

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations

As of 10 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2607.16725.

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

pith.paper-citation-record.v1
2607.16725 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T20:13:46.074080Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

70 of 70 outbound references displayed

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External citation measurements

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Outbound references

Observation e981bda3-815a-4606-b0a2-2db22aadc4ee · outbound

This paper cites Dennis , title =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Dennis , title =

Reference 1

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This paper cites 2006 , publisher =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations 2006 , publisher =

Reference 2

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations , title =

Reference 3

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This paper cites Journal of Machine Learning Research , year =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Journal of Machine Learning Research , year =

Reference 4

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations International Conference on Learning Representations , year=

Reference 5

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Unresolved cited work

Reference 6

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations 2009 , booktitle =

Reference 7

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations International Conference on Learning Representations , year=

Reference 8

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This paper cites International Conference on Learning Representations , year=.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations International Conference on Learning Representations , year=

Reference 9

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This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , year=.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , year=

Reference 10

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This paper cites International Conference on Learning Representations , year=.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations International Conference on Learning Representations , year=

Reference 11

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This paper cites Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages=.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages=

Reference 12

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This paper cites NeurIPS 2021 Workshop on Deep Generative Models and Downstream Applications , year=.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations NeurIPS 2021 Workshop on Deep Generative Models and Downstream Applications , year=

Reference 13

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Proceedings of the 38th International Conference on Machine Learning , pages =

Reference 14

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations International Conference on Learning Representations , year =

Reference 15

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations International Conference on Learning Representations , year=

Reference 16

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Unresolved cited work

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Advances in Neural Information Processing Systems , year =

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Diffusion Models Beat

Reference 19

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Advances in Neural Information Processing Systems , year=

Reference 20

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Advances in Neural Information Processing Systems , year=

Reference 21

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Elucidating Flow Matching

Reference 22

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations International Conference on Learning Representations , year=

Reference 23

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations International Conference on Learning Representations , year=

Reference 24

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Unresolved cited work

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations 2023 , booktitle =

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Advances in Neural Information Processing Systems , year=

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , year=

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations International Conference on Learning Representations , year=

Reference 29

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Proceedings of the 40th International Conference on Machine Learning , year =

Reference 30

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations and Wasserman, Larry , title =

Reference 31

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations , title =

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations arXiv preprint arXiv:2512.18971 , year=

Reference 33

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory

Reference 34

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Advances in Neural Information Processing Systems , volume=

Reference 35

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations and Boffi, Nicholas M

Reference 36

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations The Annals of Statistics , VOLUME =

Reference 37

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Journal of Machine Learning Research , volume=

Reference 38

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Observation a2cf6ab7-35e3-446f-bf6f-6b1104eabae9 · outbound

This paper cites Journal of the American Statistical Association , volume =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Journal of the American Statistical Association , volume =

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Observation fbd4c751-e070-42a1-89cc-3cb0a0f4c7e7 · outbound

This paper cites Measuring and testing dependence by correlation of distances , FJOURNAL =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Measuring and testing dependence by correlation of distances , FJOURNAL =

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Observation a6ba111e-fe31-4390-80b3-a837adbb8950 · outbound

This paper cites an unresolved cited work.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Unresolved cited work

Reference 41

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Observation 7a63d6e0-4da1-4857-8a19-b42176282990 · outbound

This paper cites The Annals of Statistics , VOLUME =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations The Annals of Statistics , VOLUME =

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Observation 2aa75416-f632-4978-8915-477e9c1ed013 · outbound

This paper cites and Bottou, L.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations and Bottou, L

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Observation e6627aa6-2a3a-4c0a-bfef-bb38668be216 · outbound

This paper cites Hierarchical text-conditional image generation with.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Hierarchical text-conditional image generation with

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Observation 866f0af8-ec0e-4bba-86fd-6b4eca33cb4b · outbound

This paper cites arXiv preprint arXiv:2511.03193 , year=.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations arXiv preprint arXiv:2511.03193 , year=

Reference 45

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Observation 409fe7a1-5138-45c5-b90a-6ac0a5935487 · outbound

This paper cites The Annals of Statistics , volume=.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations The Annals of Statistics , volume=

Reference 46

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Observation 11b2d30a-46a7-4d81-925f-9ba8ae4fbd9c · outbound

This paper cites and Gretton, Arthur and Fukumizu, Kenji and Sch\".

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations and Gretton, Arthur and Fukumizu, Kenji and Sch\"

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Observation d5ac837a-c832-4c2f-870c-9a1f93caced0 · outbound

This paper cites On the rate of convergence of a classifier based on a transformer encoder , FJOURNAL =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations On the rate of convergence of a classifier based on a transformer encoder , FJOURNAL =

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Observation 9dc03a92-529c-4141-ab4e-909f33cb1a0d · outbound

This paper cites The Annals of Statistics , VOLUME =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations The Annals of Statistics , VOLUME =

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Observation 0eb57c9a-e472-48d3-966d-a9fa20192921 · outbound

This paper cites Journal of the American Statistical Association , VOLUME =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Journal of the American Statistical Association , VOLUME =

Reference 50

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Observation 4a52125a-84fd-4c08-9fa4-8106fc61bc95 · outbound

This paper cites and Harvey, Nick and Liaw, Christopher and Mehrabian, Abbas , title =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations and Harvey, Nick and Liaw, Christopher and Mehrabian, Abbas , title =

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Observation 5fa35959-a54d-4957-93d2-d992b119e7ad · outbound

This paper cites Deep Dimension Reduction for Supervised Representation Learning , year=.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Deep Dimension Reduction for Supervised Representation Learning , year=

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Observation 31824ab7-aa6d-4c18-9c38-da3a64d16b67 · outbound

This paper cites , TITLE =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations , TITLE =

Reference 53

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Observation 3a456f0b-85b3-44e9-94b2-d129ed135ddb · outbound

This paper cites an unresolved cited work.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Unresolved cited work

Reference 54

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Observation d54deaac-800e-4cea-90b7-4a4241cadf42 · outbound

This paper cites The Annals of Statistics , VOLUME =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations The Annals of Statistics , VOLUME =

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations arXiv preprint arXiv:2603.04223 , year=

Reference 56

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Observation 0fbb06cc-7aff-4700-9b4e-33562d4d9ff2 · outbound

This paper cites Neural Networks , volume =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Neural Networks , volume =

Reference 57

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Observation c8d6b379-85ed-4219-89cc-5a3f98b07303 · outbound

This paper cites Convergence Analysis of Flow Matching in Latent Space with Transformers.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Convergence Analysis of Flow Matching in Latent Space with Transformers

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Observation 8f6d9a5c-6bdc-457f-956d-cce3208e0aa1 · outbound

This paper cites Latent Schr.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Latent Schr

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Observation e06c59c7-c408-4f7f-9fa3-bc6e641de101 · outbound

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations arXiv preprint arXiv:2402.01460 , year=

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Observation 1dc65c33-5e83-4a2a-b996-013e482b68a4 · outbound

This paper cites Conditional Stochastic Interpolation for Generative Learning.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Conditional Stochastic Interpolation for Generative Learning

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Observation 41059bd0-ef53-4b3f-ad56-b39d70f01169 · outbound

This paper cites Convergence of Continuous Normalizing Flows for Learning Probability Distributions.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Convergence of Continuous Normalizing Flows for Learning Probability Distributions

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Observation 032f7b07-10f8-4cc8-b12a-9c7811349794 · outbound

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations IEEE Transactions on Pattern Analysis and Machine Intelligence , volume=

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Observation a9a0824d-707c-4641-a4ce-cf02c1df940d · outbound

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Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations and Baraniuk, Richard G

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Observation 53324f27-d2a6-4c80-aa4c-be0e84651122 · outbound

This paper cites ExDiffusion: Classifier-Guidance Diffusion Model for Extreme Load Scenario Generation With Extreme Value Theory , year=.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations ExDiffusion: Classifier-Guidance Diffusion Model for Extreme Load Scenario Generation With Extreme Value Theory , year=

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Observation 58fa24b7-9334-400b-a9c2-dec8b7ddb211 · outbound

This paper cites 2003 , edition =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations 2003 , edition =

Reference 66

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Observation 40f5fb28-6125-4473-9403-2f8e21b2d5c2 · outbound

This paper cites 2002 , publisher=.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations 2002 , publisher=

Reference 67

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Observation 40b33a33-6150-40b4-aa60-a586acea5cba · outbound

This paper cites Brownian Motion, Martingales, and Stochastic Calculus , SERIES =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations Brownian Motion, Martingales, and Stochastic Calculus , SERIES =

Reference 68

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Observation 2a6d134b-6f41-482f-88f9-5912ccc963fa · outbound

This paper cites , TITLE =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations , TITLE =

Reference 69

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Observation c2e94844-acb8-4b8e-b40e-dd922c0e4ebe · outbound

This paper cites , TITLE =.

Semi-Supervised Conditional Generative Learning through Stochastic Interpolation and Sufficient Representations , TITLE =

Reference 70

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Pith citing papers

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