Paper Citation Record · LEDGER

Provenance Tracking in Large-Scale Machine Learning Systems

As of 8 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 2 inbound Pith citation observations for arXiv:2507.01075.

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

pith.paper-citation-record.v1
2507.01075 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:10:34.559971Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T17:53:42.038769Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

44 of 44 outbound references displayed

verified exact3
verified fuzzy31
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation b996b832-e610-49ef-b09f-ea32b3d67e9b · outbound

This paper cites Pushing the frontiers in climate modelling and analysis with machine learning.

Provenance Tracking in Large-Scale Machine Learning Systems Pushing the frontiers in climate modelling and analysis with machine learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.996575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 60edec11-8c77-4875-9588-d4c8c2881f97 · outbound

This paper cites Machine Learning for the Physics of Climate.

Provenance Tracking in Large-Scale Machine Learning Systems Machine Learning for the Physics of Climate

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:10:34.661328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7110f132-dab1-4a3e-b953-709792b14dec · outbound

This paper cites Tackling climate change with machine learning.

Provenance Tracking in Large-Scale Machine Learning Systems Tackling climate change with machine learning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.987430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6a88a8d0-ab82-4310-ba81-d50fe400170b · outbound

This paper cites Provenance: a future history.

Provenance Tracking in Large-Scale Machine Learning Systems Provenance: a future history

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.978672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eb9dba89-3128-4c77-aff1-c247bdd3edae · outbound

This paper cites Advances, challenges and opportunities in creating data for trustworthy ai.

Provenance Tracking in Large-Scale Machine Learning Systems Advances, challenges and opportunities in creating data for trustworthy ai

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.969941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 588be5e1-41c3-45b2-b98b-b1e786305ba1 · outbound

This paper cites What information is required for explainable ai?: A provenance-based research agenda and future challenges.

Provenance Tracking in Large-Scale Machine Learning Systems What information is required for explainable ai?: A provenance-based research agenda and future challenges

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.960919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5db22906-5a15-4da6-bb5b-aca90954950e · outbound

This paper cites Leakage and the Reproducibility Crisis in ML-based Science.

Provenance Tracking in Large-Scale Machine Learning Systems Leakage and the Reproducibility Crisis in ML-based Science

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T21:10:34.438802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 835427fb-640e-44d6-8652-4d9895c48229 · outbound

This paper cites Komadu: A capture and visual- ization system for scientific data provenance.

Provenance Tracking in Large-Scale Machine Learning Systems Komadu: A capture and visual- ization system for scientific data provenance

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.951999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b2228be4-6b43-4525-b8ae-87ca959dd904 · outbound

This paper cites Accelerating the machine learning lifecycle with mlflow.

Provenance Tracking in Large-Scale Machine Learning Systems Accelerating the machine learning lifecycle with mlflow

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.943151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6b5173cb-b0d7-4d7f-b32b-561e003233bd · outbound

This paper cites The prov-json serialization.

Provenance Tracking in Large-Scale Machine Learning Systems The prov-json serialization

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.934151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fbb2ba83-c9d6-4310-b51f-246e977c3805 · outbound

This paper cites Enabling provenance tracking in workflow management systems.

Provenance Tracking in Large-Scale Machine Learning Systems Enabling provenance tracking in workflow management systems

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.924557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f4a4b5cb-165e-494d-9920-6ecb9b25fd74 · outbound

This paper cites A software ecosystem for multi-level provenance management in large-scale scientific workflows for ai applications.

Provenance Tracking in Large-Scale Machine Learning Systems A software ecosystem for multi-level provenance management in large-scale scientific workflows for ai applications

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.916129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1fbcfc09-b8e6-42c7-a5e7-d565fb7ef3cb · outbound

This paper cites The w3c prov family of specifications for modelling provenance metadata.

Provenance Tracking in Large-Scale Machine Learning Systems The w3c prov family of specifications for modelling provenance metadata

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.907583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 732ca248-8d8e-4daa-9e04-f948b060878d · outbound

This paper cites Prov-dm: The prov data model.

Provenance Tracking in Large-Scale Machine Learning Systems Prov-dm: The prov data model

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.898261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c6ca7967-694d-43d7-b161-6db428fb42d8 · outbound

This paper cites Prov-n: The provenance notation.

Provenance Tracking in Large-Scale Machine Learning Systems Prov-n: The provenance notation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.888738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a4d0ae9b-83fa-4d00-9989-edda04f05c09 · outbound

This paper cites Provenance data in the machine learning lifecycle in computational science and engineering.

Provenance Tracking in Large-Scale Machine Learning Systems Provenance data in the machine learning lifecycle in computational science and engineering

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.879108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2c2b900e-0454-4bee-b933-b10e78547bdd · outbound

This paper cites Efficient runtime capture of multiworkflow data using provenance.

Provenance Tracking in Large-Scale Machine Learning Systems Efficient runtime capture of multiworkflow data using provenance

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.870211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 236721c5-7dba-4b7f-aeb6-4aa24037729a · outbound

This paper cites ML-Schema: Exposing the Semantics of Machine Learning with Schemas and Ontologies.

Provenance Tracking in Large-Scale Machine Learning Systems ML-Schema: Exposing the Semantics of Machine Learning with Schemas and Ontologies

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T21:10:34.474405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da0be126-c13c-471d-af1d-d6bdc6a9f344 · outbound

This paper cites Workflow provenance in the lifecycle of scientific machine learning.

Provenance Tracking in Large-Scale Machine Learning Systems Workflow provenance in the lifecycle of scientific machine learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.860833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0a7add35-5f47-49e5-baf1-2912ebc4dd23 · outbound

This paper cites Mlflow2prov: extracting provenance from machine learning experiments.

Provenance Tracking in Large-Scale Machine Learning Systems Mlflow2prov: extracting provenance from machine learning experiments

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.850893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 08047694-3c9f-4637-8d18-042e8019d30f · outbound

This paper cites Harris, Frederick C., Chenhao Li, Jiyin Zhang, and Xiaogang Ma.

Provenance Tracking in Large-Scale Machine Learning Systems Harris, Frederick C., Chenhao Li, Jiyin Zhang, and Xiaogang Ma

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.841691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 55a7d411-39f7-4005-9121-29b0692d7070 · outbound

This paper cites Interoperability for provenance-aware databases using {PROV} and {JSON}.

Provenance Tracking in Large-Scale Machine Learning Systems Interoperability for provenance-aware databases using {PROV} and {JSON}

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.832184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 43ecfe93-80df-44af-8bfc-de7c2eab12c5 · outbound

This paper cites Provenance supporting hyperparameter analysis in deep neural networks.

Provenance Tracking in Large-Scale Machine Learning Systems Provenance supporting hyperparameter analysis in deep neural networks

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.821512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c6a5d8d7-5708-4698-947e-6bafb6f9c64b · outbound

This paper cites Data provenance based system for classification and linear regression in distributed machine learning.

Provenance Tracking in Large-Scale Machine Learning Systems Data provenance based system for classification and linear regression in distributed machine learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.810864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation df2e4689-402e-40f8-9796-e7be648747cd · outbound

This paper cites Lima: Fine-grained lin- eage tracing and reuse in machine learning systems.

Provenance Tracking in Large-Scale Machine Learning Systems Lima: Fine-grained lin- eage tracing and reuse in machine learning systems

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.800855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 93553de5-1cb6-4125-872d-cb57257fa949 · outbound

This paper cites AuditMAI: Towards An Infrastructure for Continuous AI Auditing.

Provenance Tracking in Large-Scale Machine Learning Systems AuditMAI: Towards An Infrastructure for Continuous AI Auditing

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:10:34.629187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4bfe1915-6b78-4e0a-923e-e3d0be211300 · outbound

This paper cites Recording provenance of workflow runs with ro-crate.

Provenance Tracking in Large-Scale Machine Learning Systems Recording provenance of workflow runs with ro-crate

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.790879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation deb7fc73-b883-430e-ba19-a4e6a245b6fb · outbound

This paper cites Packaging research artefacts with ro-crate.

Provenance Tracking in Large-Scale Machine Learning Systems Packaging research artefacts with ro-crate

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.782027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4bccf0ad-9be6-48de-8dbb-d824ad6fc7de · outbound

This paper cites Towards lightweight data integration using multi- workflow provenance and data observability.

Provenance Tracking in Large-Scale Machine Learning Systems Towards lightweight data integration using multi- workflow provenance and data observability

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.772599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6b843dc1-402d-451c-ba04-da12b24aa10f · outbound

This paper cites Work- flow provenance in the computing continuum for responsible, trustworthy, and energy-efficient ai.

Provenance Tracking in Large-Scale Machine Learning Systems Work- flow provenance in the computing continuum for responsible, trustworthy, and energy-efficient ai

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.763089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation acd8f5f2-086f-4b35-8bc3-dc376f124285 · outbound

This paper cites Experiment tracking with weights and biases, 2020.

Provenance Tracking in Large-Scale Machine Learning Systems Experiment tracking with weights and biases, 2020

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T21:10:34.517902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9b1827b-4c18-453f-8a30-83628a3e9921 · outbound

This paper cites A graph data model-based micro-provenance approach for multi-level provenance exploration in end-to-end climate workflows.

Provenance Tracking in Large-Scale Machine Learning Systems A graph data model-based micro-provenance approach for multi-level provenance exploration in end-to-end climate workflows

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.746006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation de803277-ae85-410e-af86-00bf4db2f7d5 · outbound

This paper cites Evalua- tion of pre-training large language models on leadership-class supercomputers.

Provenance Tracking in Large-Scale Machine Learning Systems Evalua- tion of pre-training large language models on leadership-class supercomputers

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.735838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9972bac3-9c44-4aa7-a32f-e63e40508d6c · outbound

This paper cites Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei.

Provenance Tracking in Large-Scale Machine Learning Systems Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T21:10:34.527576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2da67b2c-65f6-4771-b765-0a603d6e5abb · outbound

This paper cites Rae, Oriol Vinyals, and Laurent Sifre.

Provenance Tracking in Large-Scale Machine Learning Systems Rae, Oriol Vinyals, and Laurent Sifre

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T21:10:34.530840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 550ea848-aaca-4757-860c-0806b1d134d3 · outbound

This paper cites Rush, Boaz Barak, Teven Le Scao, Aleksandra Piktus, Nouamane Tazi, Sampo Pyysalo, Thomas Wolf, and Colin Raffel.

Provenance Tracking in Large-Scale Machine Learning Systems Rush, Boaz Barak, Teven Le Scao, Aleksandra Piktus, Nouamane Tazi, Sampo Pyysalo, Thomas Wolf, and Colin Raffel

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T21:10:34.533845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74a587a7-5247-42d3-8615-ff941d66f250 · outbound

This paper cites Netcdf user’s guide, 1993.

Provenance Tracking in Large-Scale Machine Learning Systems Netcdf user’s guide, 1993

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.706344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d9172937-ac00-4f87-a692-bd26dae5f2e3 · outbound

This paper cites https://zarr.dev/.

Provenance Tracking in Large-Scale Machine Learning Systems https://zarr.dev/

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.696671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5230a602-c93b-4aa4-843a-a77107ec64d4 · outbound

This paper cites Trustworthy Provenance for Big Data Science: a Modular Architecture Leveraging Blockchain in Federated Settings.

Provenance Tracking in Large-Scale Machine Learning Systems Trustworthy Provenance for Big Data Science: a Modular Architecture Leveraging Blockchain in Federated Settings

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:10:34.615000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c9ae2e5c-5dec-4f52-97b7-70b466f1d732 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Provenance Tracking in Large-Scale Machine Learning Systems An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T21:10:34.547718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bd0dcbd-e1c9-4fe4-96a3-d0704d33be44 · outbound

This paper cites The modis cloud optical and microphysical products: Collec- tion 6 updates and examples from terra and aqua.IEEE Transactions on Geoscience and Remote Sensing, 55(1):502–525, 2016.

Provenance Tracking in Large-Scale Machine Learning Systems The modis cloud optical and microphysical products: Collec- tion 6 updates and examples from terra and aqua.IEEE Transactions on Geoscience and Remote Sensing, 55(1):502–525, 2016

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:10:34.686543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eab06664-ab32-41e4-b955-37d1f8b77184 · outbound

This paper cites Swin transformer v2: Scaling up capacity and resolution.

Provenance Tracking in Large-Scale Machine Learning Systems Swin transformer v2: Scaling up capacity and resolution

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T21:10:34.553490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c5fa92a-2a30-424e-890f-ca9bb02a7b84 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Provenance Tracking in Large-Scale Machine Learning Systems Masked autoencoders are scalable vision learners

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T21:10:34.557139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8aec9951-9413-412b-bd28-0f5900368c36 · outbound

This paper cites PyTorch Distributed: Experiences on Accelerating Data Parallel Training.

Provenance Tracking in Large-Scale Machine Learning Systems PyTorch Distributed: Experiences on Accelerating Data Parallel Training

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T21:10:34.559971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 53193c9f-8f8b-42d9-8ff2-eab22b6be886 · inbound

Provenance Tracking in AI Compilers through the Lens of Coalgebra cites this paper.

Provenance Tracking in AI Compilers through the Lens of Coalgebra Provenance Tracking in Large-Scale Machine Learning Systems

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-08-07T00:51:06.350905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 13d66bcc-0533-4efa-ab7e-1d4e4c6fc6d3 · inbound

AuditWeave: A Tamper-Evident, Auditor-Navigable Evidence Layer for AI-Assisted and Data-Transformation Workflows cites this paper.

AuditWeave: A Tamper-Evident, Auditor-Navigable Evidence Layer for AI-Assisted and Data-Transformation Workflows Provenance Tracking in Large-Scale Machine Learning Systems

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T17:53:42.038769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.