Paper Citation Record · LEDGER

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations

As of 10 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2606.00248.

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

pith.paper-citation-record.v1
2606.00248 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T22:28:27.642338Z

measured 27 of 27 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

27 of 27 outbound references displayed

verified exact1
verified fuzzy0
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9703d9f8-ccfa-4af7-b5ca-0899ff6f3136 · outbound

This paper cites Memorization to generalization: Emergence of diffusion models from associative memory.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Memorization to generalization: Emergence of diffusion models from associative memory

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T22:32:44.252456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 719073b3-8227-4b50-8cde-b857c611fc0b · outbound

This paper cites Frontiers in Neuroscience , year=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Frontiers in Neuroscience , year=

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a69f99aa-a038-44ed-a7b5-6d37b99bebb7 · outbound

This paper cites Advances in neural information processing systems , volume=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Advances in neural information processing systems , volume=

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5514c64f-ae1f-470c-b0f6-0c181dda9c67 · outbound

This paper cites 41st Annual Meeting of the Cognitive Science Society , year=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations 41st Annual Meeting of the Cognitive Science Society , year=

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d57d3258-43e1-408a-a813-25a74db5fdc2 · outbound

This paper cites Proceedings of the AAAI Symposium Series , volume=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Proceedings of the AAAI Symposium Series , volume=

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ad441e2-75f8-407c-85e4-e049b2dee06d · outbound

This paper cites 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , pages=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , pages=

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1457bc4-f8de-4580-98e2-b6bd9cbb944c · outbound

This paper cites 2023 , eprint=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations 2023 , eprint=

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7647bd70-dece-4225-bd47-20f3119de0c5 · outbound

This paper cites 2021 , eprint=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations 2021 , eprint=

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc91dea6-d54d-4105-8510-b34149fdaf68 · outbound

This paper cites Proceedings of the Annual Meeting of the Cognitive Science Society , volume=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Proceedings of the Annual Meeting of the Cognitive Science Society , volume=

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8529989f-edf1-46b3-bece-24cdc545369b · outbound

This paper cites Proceedings of the Annual Meeting of the Cognitive Science Society , volume=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Proceedings of the Annual Meeting of the Cognitive Science Society , volume=

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e413758e-fef0-4d14-b39c-a1a39ffb0ee1 · outbound

This paper cites Frontiers in Neuroscience , volume=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Frontiers in Neuroscience , volume=

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 189c2dc2-38d6-4f00-94b0-0ec1f7fa1b9c · outbound

This paper cites Neural Computation , volume=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Neural Computation , volume=

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3748e5d5-0adb-4298-9eee-0e9427556ea5 · outbound

This paper cites Memory in Plain Sight: Surveying the Uncanny Resemblances of Associative Memories and Diffusion Models.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Memory in Plain Sight: Surveying the Uncanny Resemblances of Associative Memories and Diffusion Models

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T22:32:44.255237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4ae05f08-b99a-407f-baf8-cabf13c86215 · outbound

This paper cites Annual Meeting of the Cognitive Science Society , year=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Annual Meeting of the Cognitive Science Society , year=

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05115282-cd6a-4428-9009-08257fdc599f · outbound

This paper cites Nature , year=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Nature , year=

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5ce14b3-101b-4c49-9d27-b21f9add4b54 · outbound

This paper cites Mathematical programming , volume=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Mathematical programming , volume=

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 448c8c8a-0b29-42c5-be23-2d89d72c3077 · outbound

This paper cites Energy matching: Unifying flow matching and energy-based models for generative modeling.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Energy matching: Unifying flow matching and energy-based models for generative modeling

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T22:32:44.249813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 28932a8b-7db4-4100-a97b-6e4999f43950 · outbound

This paper cites Stewart and Yichuan Tang and Chris Eliasmith , title=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Stewart and Yichuan Tang and Chris Eliasmith , title=

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4efd626f-f5e1-4322-aeb5-533f0b9623d0 · outbound

This paper cites , author=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations , author=

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf390d91-9636-457e-a3a0-d6c7262287fc · outbound

This paper cites Hopfield Networks is All You Need.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Hopfield Networks is All You Need

Reference 20

Resolution: metadata mismatch; local_arxiv, observed 2026-06-28T22:32:44.244906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d29fffe9-fc42-49f6-a738-dc9cde16c4eb · outbound

This paper cites Flow Matching for Generative Modeling.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Flow Matching for Generative Modeling

Reference 21

Resolution: metadata mismatch; local_arxiv, observed 2026-06-28T22:32:44.242713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6e784f68-49bb-4186-8f08-00f13285bf8d · outbound

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

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations International Conference on Learning Representations , volume=

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2123e5c2-e0a5-4331-b060-7d937450cbc4 · outbound

This paper cites , title =.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations , title =

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b131226-d82d-4a51-b6a5-ef47c7457ee6 · outbound

This paper cites Artificial Intelligence Review , volume=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Artificial Intelligence Review , volume=

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ffce7df-697c-484d-91d5-b21ca6fd8ea1 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Advances in Neural Information Processing Systems , volume=

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3ce56aa-a07c-4910-9fc0-5ba3544ed770 · outbound

This paper cites 34th Conference on Uncertainty in Artificial Intelligence 2018, UAI 2018 , pages=.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations 34th Conference on Uncertainty in Artificial Intelligence 2018, UAI 2018 , pages=

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-28T22:28:27.642338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7aec6a02-8f05-414e-a221-2cad9ab1a9d4 · outbound

This paper cites Increasing Expressivity of a Hyperspherical VAE.

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations Increasing Expressivity of a Hyperspherical VAE

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:32:44.247274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.