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Paper Citation Record · LEDGER

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face

As of 10 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2607.21738.

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

pith.paper-citation-record.v1
2607.21738 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T06:55:49.137073Z

measured 20 of 20 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

20 of 20 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 38f2bd90-0f16-4089-94e9-808646005110 · outbound

This paper cites Aspirations and practice of ml model documentation: Moving the needle with nudging and traceability.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Aspirations and practice of ml model documentation: Moving the needle with nudging and traceability

Reference 4

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no resolver link, observed 2026-08-01T06:55:49.070066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:55:49.070066Z digest=sha256:f2a2619af818fb6cbea8dce830839a53fef81aa16038289b44c2e714f1ecb292

Observation 7d058a29-3ac1-4f6b-adc1-ae1ce39a0d17 · outbound

This paper cites From Hugging Face to GitHub: Tracing License Drift in the Open-Source AI Ecosystem.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face From Hugging Face to GitHub: Tracing License Drift in the Open-Source AI Ecosystem

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:55:49.091977Z digest=sha256:2bc04b8c44833891b3e6d6185da97c5eaab69b3e49b6ec1e2d98bb5505c13f8d

Observation 08b3e078-b511-40e7-be84-879d8979bb21 · outbound

This paper cites An empirical study of artifacts and security risks in the pre-trained model supply chain.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face An empirical study of artifacts and security risks in the pre-trained model supply chain

Reference 10

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:55:49.096205Z digest=sha256:6243a8d3603c3aa9363dd445d3d283ef56c12791873e7e830ee2729d22c28710

Observation ed7061dc-abb5-4590-96a5-757fbdd31334 · outbound

This paper cites Anatomy of a Machine Learning Ecosystem: 2 Million Models on Hugging Face.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Anatomy of a Machine Learning Ecosystem: 2 Million Models on Hugging Face

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:55:49.104500Z digest=sha256:612f1b59cd7676d5b45359295afa55acbd8d9478d93cb8a3803293b717f89420

Observation 8a4b205f-ca4d-4eaa-9dbc-f14bec37e481 · outbound

This paper cites Ai transparency atlas: Framework, scoring, and real-time model card evaluation pipeline.arXiv preprint arXiv:2512.12443,.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Ai transparency atlas: Framework, scoring, and real-time model card evaluation pipeline.arXiv preprint arXiv:2512.12443,

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:55:49.108644Z digest=sha256:587667c34c50d6330b4cb318757c5daf62a8aa54841cc6f3d4c91bdcacc50854

Observation be8a2adb-744d-4dd5-a8b7-ce9a3d2cc8a3 · outbound

This paper cites Building an Open AIBOM Standard in the Wild.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Building an Open AIBOM Standard in the Wild

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:55:49.113052Z digest=sha256:9d56e6fc416528817fcf426725f221813b1584625a8230e3b460a6ebb0b5214f

Observation 992c91c7-978d-4849-839f-1773d3cbdd37 · outbound

This paper cites OmniBOR: A System for Automatic, Verifiable Artifact Resolution across Software Supply Chains.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face OmniBOR: A System for Automatic, Verifiable Artifact Resolution across Software Supply Chains

Reference 15

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source=pdf_text observed=2026-08-01T06:55:49.117313Z digest=sha256:e09e66df80fb25ef1e822a6e52948e6f8ac7c989f11c54a098fc7caac4440711

Observation c737b59c-26c6-48e2-aaba-7a97e2b42cdf · outbound

This paper cites Bomfather: An eBPF-based Kernel-level Monitoring Framework for Accurate Identification of Unknown, Unused, and Dynamically Loaded Dependencies in Modern Software Supply Chains.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Bomfather: An eBPF-based Kernel-level Monitoring Framework for Accurate Identification of Unknown, Unused, and Dynamically Loaded Dependencies in Modern Software Supply Chains

Reference 16

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source=pdf_text observed=2026-08-01T06:55:49.121387Z digest=sha256:bbe07e1b175fab64b6e66f62d76982f7245829fa02fcd8419563ddf9e0e63fc2

Observation 291b4501-c867-4354-96af-2820e2ae35cc · outbound

This paper cites Aibomgen: Generating an ai bill of materials for secure, transparent, and compliant model training.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Aibomgen: Generating an ai bill of materials for secure, transparent, and compliant model training

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:55:49.125395Z digest=sha256:a293bb911a75ada45495ba4422248f2009f78f256442f014d1f5539679f1f9c5

Observation 1a8ce792-8cce-4772-9115-d23b3a588fdf · outbound

This paper cites Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on Hugging Face.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on Hugging Face

Reference 18

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source=pdf_text observed=2026-08-01T06:55:49.129164Z digest=sha256:0e6f985e3d4c0ab86fdbf30e430d2a462717039ffbcdeb3a1572bf6bcf7958aa

Observation 8c3370a9-524d-4561-8839-a0cc812fe07c · outbound

This paper cites Software dependencies 2.0: An empir- ical study of reuse and integration of pre-trained models in open-source projects.arXiv preprint arXiv:2509.06085,.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Software dependencies 2.0: An empir- ical study of reuse and integration of pre-trained models in open-source projects.arXiv preprint arXiv:2509.06085,

Reference 19

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source=pdf_text observed=2026-08-01T06:55:49.133088Z digest=sha256:4508d304ed51f7c4c7068f003f30f8311114946b6aa5dd74e63d040b97dec13f

Observation 1f9393af-8726-4348-9f5c-c551b73d9acd · outbound

This paper cites A Survey of Large Language Models.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face A Survey of Large Language Models

Reference 20

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:55:49.137073Z digest=sha256:d7711803725205ab8119c043dc288c9cdf467ff699321b4a24768d2bfb3d12c6

Observation 23397de7-f0f1-4e01-a328-920901b89380 · outbound

This paper cites Implementing ai bill of materials (ai bom) with spdx 3.0: A comprehensive guide to creating ai and dataset bill of materials.arXiv preprint arXiv:2504.16743,.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Implementing ai bill of materials (ai bom) with spdx 3.0: A comprehensive guide to creating ai and dataset bill of materials.arXiv preprint arXiv:2504.16743,

Reference 1995

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source=pdf_text observed=2026-08-01T06:55:49.065530Z digest=sha256:6f19fe4e862516c42544d98627932b52f13511bac973c7be89e5a2f792168bd1

Observation f01c9165-d818-4a95-b3d0-b96c12bdef29 · outbound

This paper cites Joel Casta˜ no, Rafael Caba˜ nas, Antonio Salmer´ on, David Lo, and Silverio Mart ´ ınez-Fern´ andez.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Joel Casta˜ no, Rafael Caba˜ nas, Antonio Salmer´ on, David Lo, and Silverio Mart ´ ınez-Fern´ andez

Reference 2006

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source=pdf_text observed=2026-08-01T06:55:49.078816Z digest=sha256:076356f923bbcfcd3428be6ee01645dfdce065c6e2a62f1b5101aa9ddbe11270

Observation b471f9ac-8734-4e86-85d9-ff5d25c17c1c · outbound

This paper cites Modelgo: A practical tool for machine learning license analysis.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Modelgo: A practical tool for machine learning license analysis

Reference 2021

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:55:49.082978Z digest=sha256:c3b52c7e3fd2a372b0bd2ed759841df08e87760c05aa27cb634e46197a2da3b8

Observation 16c53cfc-15de-4e8f-8694-791b68c26850 · outbound

This paper cites "I see models being a whole other thing": An Empirical Study of Pre-Trained Model Naming Conventions and A Tool for Enhancing Naming Consistency.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face "I see models being a whole other thing": An Empirical Study of Pre-Trained Model Naming Conventions and A Tool for Enhancing Naming Consistency

Reference 2022

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:55:49.100139Z digest=sha256:87d5fd20b79b60e91d905a80b9584ec14b066de4ed5d117b17439f5b33b8dbde

Observation b7fefc62-0b5e-445b-8f67-421b3cb366fe · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face On the Opportunities and Risks of Foundation Models

Reference 2023

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source=pdf_text observed=2026-08-01T06:55:49.074237Z digest=sha256:d53f69cdaa239047d3bd93305955308add7374825717816c6d2d10f51f5d0bdc

Observation 7a070ae8-414d-4da4-b7a1-ad172ee62b94 · outbound

This paper cites Empirical char- acterization of logging smells in machine learning code.arXiv preprint arXiv:2603.23769,.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Empirical char- acterization of logging smells in machine learning code.arXiv preprint arXiv:2603.23769,

Reference 2024

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source=pdf_text observed=2026-08-01T06:55:49.087296Z digest=sha256:af5feb57146566c0ab8e960f0925ecffb58339aa81aa73be71cdf6fc3f66c8d0

Observation 4e6fc1a9-4ca5-4faa-8632-bdd15aaa9378 · outbound

This paper cites On the synchronization between hugging face pre-trained language models and their upstream github repository.arXiv preprint arXiv:2508.10157,.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face On the synchronization between hugging face pre-trained language models and their upstream github repository.arXiv preprint arXiv:2508.10157,

Reference 2025

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source=pdf_text observed=2026-08-01T06:55:49.056015Z digest=sha256:669278ea095bd4c5c447d7d4175e842c3d102a46958734b1e639668cd4e31abf

Observation 4de5cb20-1c06-44d1-a5d1-0d651af051fe · outbound

This paper cites Version v1.

When Model Release Meets Model Reuse: Producer-Consumer Misalignment in Hugging Face Version v1

Reference 2026

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source=pdf_text observed=2026-08-01T06:55:49.061151Z digest=sha256:2d3ca12d9860d35113e5ed95566df647be13cf781d49c62de6992a8831a573fb

Pith citing papers

No inbound Pith citation observations are available.