Paper Citation Record · LEDGER

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs

As of 4 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2606.26492.

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

pith.paper-citation-record.v1
2606.26492 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T04:45:46.785605Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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

39 of 39 outbound references displayed

verified exact8
verified fuzzy0
unresolved10
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malformed identifier5
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6f6df191-1781-45e2-985b-938aac5df94f · outbound

This paper cites Phoenix: automated data-driven synthesis of repairs for static analysis violations.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Phoenix: automated data-driven synthesis of repairs for static analysis violations

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T04:48:59.770093Z

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Observation fcf6ef1f-8952-4a5c-a75c-1d005c3d3d7c · outbound

This paper cites Misbehaviour prediction for autonomous driving sys- tems.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Misbehaviour prediction for autonomous driving sys- tems

Reference 2

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Observation 35c25b50-c7e7-4b1b-aede-fbf65a1a8432 · outbound

This paper cites Visualizing the loss landscape of neural nets,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Visualizing the loss landscape of neural nets,

Reference 3

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Source-reported events for the cited work

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Observation 0c2cd43a-50b7-493d-b26e-976ed5f2c929 · outbound

This paper cites Ferreira, Rui Abreu, and Pedro Cruz.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Ferreira, Rui Abreu, and Pedro Cruz

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T04:48:59.721257Z

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Observation f7d13938-eb82-419e-940b-e99b07a67b4c · outbound

This paper cites Recognizing developers' emotions while programming , isbn =.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Recognizing developers' emotions while programming , isbn =

Reference 5

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Observation a25ea324-adc8-48ef-9634-d7610e4b1dd1 · outbound

This paper cites Refty: refinement types for valid deep learning models,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Refty: refinement types for valid deep learning models,

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T04:48:59.703120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 43d718fd-eda6-407d-b264-97f38795c426 · outbound

This paper cites InProceedings of the 44th International Conference on Software Engineering (Pittsburgh, Pennsylvania)(ICSE ’22).

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs InProceedings of the 44th International Conference on Software Engineering (Pittsburgh, Pennsylvania)(ICSE ’22)

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T04:48:59.726914Z

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Observation a87a246e-87be-4f2b-9d06-4d8d60a5464c · outbound

This paper cites 2025.IRFuzzer: Specialized Fuzzing for LLVM Backend Code Generation.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs 2025.IRFuzzer: Specialized Fuzzing for LLVM Backend Code Generation

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T04:48:59.704696Z

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Observation f8a84aae-6ff1-4ab7-9e7b-8a3bdb244971 · outbound

This paper cites Coverage-enhanced fault diagnosis for deep learning programs: A learning-based approach with hybrid metrics,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Coverage-enhanced fault diagnosis for deep learning programs: A learning-based approach with hybrid metrics,

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-26T04:48:59.767240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ea96adc7-0eee-4ee2-ad87-a95cc843942c · outbound

This paper cites From Local Explanations to Global Understanding with Explainable AI for Trees.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs From Local Explanations to Global Understanding with Explainable AI for Trees

Reference 10

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Source-reported events for the cited work

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Observation 8740561e-9f84-4486-95b6-12bb4d23ddc7 · outbound

This paper cites Cross-project defect prediction: A large scale experiment on data vs. domain vs. process,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Cross-project defect prediction: A large scale experiment on data vs. domain vs. process,

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-26T04:48:59.713323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ced5b12e-0b6c-4646-9097-d30a16cea592 · outbound

This paper cites IEEE Transactions on Software Engineering43(2), 185–204 (2017) https://doi.org/10.1109/TSE.2016.2584053 44.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs IEEE Transactions on Software Engineering43(2), 185–204 (2017) https://doi.org/10.1109/TSE.2016.2584053 44

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T04:48:59.763991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d89bab5e-298d-48cc-9e84-47848e51517c · outbound

This paper cites Roberts, V.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Roberts, V

Reference 13

Resolution: metadata mismatch; doi, observed 2026-06-26T04:48:59.709868Z

Source-reported events for the cited work

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Observation 1bda1503-9f50-4e5b-8a2d-c1b86f9d3692 · outbound

This paper cites An empirical study of the impact of data splitting decisions on the performance of AIOps solutions,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs An empirical study of the impact of data splitting decisions on the performance of AIOps solutions,

Reference 14

Resolution: verified exact; doi, observed 2026-06-26T04:48:59.695268Z

Source-reported events for the cited work

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Observation d9251d02-65e6-4c26-b5ee-70df683a4d46 · outbound

This paper cites Traceability transformed: Generating more accurate links with pre-trained BERT models.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Traceability transformed: Generating more accurate links with pre-trained BERT models

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T04:48:59.735451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 156c739a-6612-48d9-88b3-f8ebc27ade28 · outbound

This paper cites UMLAUT: Debugging deep learning programs using program structure and model behavior,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs UMLAUT: Debugging deep learning programs using program structure and model behavior,

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-06-26T04:48:59.707704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 64fa014c-609f-4f94-8fe2-bb7284692b80 · outbound

This paper cites Jahan,Replication Package for the Evaluation Strategy Gap Study, https : / / github.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Jahan,Replication Package for the Evaluation Strategy Gap Study, https : / / github

Reference 17

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Source-reported events for the cited work

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Observation 773e3656-70ec-41f6-9f7e-d4cdb687751a · outbound

This paper cites Chembakottu, H.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Chembakottu, H

Reference 18

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Observation e8e978c3-cc40-4001-91c8-142143a56ed6 · outbound

This paper cites title =.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs title =

Reference 19

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Observation 5b57162b-5c53-4a4b-8844-dbbc967af0e9 · outbound

This paper cites Generalized linear models,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Generalized linear models,

Reference 20

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Observation 994ea424-a6cd-4f1c-b28b-4b0bc22a4f25 · outbound

This paper cites An investigation into neural net optimization via hessian eigenvalue density,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs An investigation into neural net optimization via hessian eigenvalue density,

Reference 21

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Observation 93698bcd-ead2-4385-b7f1-4090a1ec03d9 · outbound

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Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs 2025.Compiler Optimization Testing Based on Optimization-Guided Equivalence Transformations

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-06-26T04:48:59.718421Z

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Observation dfc8da54-3402-47f0-9240-fbbabd33556b · outbound

This paper cites 2011, Neural Comput., 23, 1661, 10.1162/NECO\_a\_00142.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs 2011, Neural Comput., 23, 1661, 10.1162/NECO\_a\_00142

Reference 23

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Observation 1c5ac612-a9e2-42d2-8d4c-c91023020a56 · outbound

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Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Deep learning via hessian-free optimization,

Reference 24

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Source-reported events for the cited work

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Observation 3cdaa2a7-dee8-4957-810a-7b8432c70ef2 · outbound

This paper cites Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability

Reference 25

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Observation b7a64cbf-31af-4c16-8f7b-6f304081e348 · outbound

This paper cites Understanding gradient descent on the edge of stability in deep learning,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Understanding gradient descent on the edge of stability in deep learning,

Reference 26

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Observation c75d0a5c-6bb6-4895-a9e2-7e63564ac2df · outbound

This paper cites A Loss Curvature Perspective on Training Instability in Deep Learning.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs A Loss Curvature Perspective on Training Instability in Deep Learning

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:59:52.032131Z

Source-reported events for the cited work

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Observation f9a9126c-25d7-4936-adcd-54ad18b82318 · outbound

This paper cites Cockpit: A practical debugging tool for the training of deep neural networks,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Cockpit: A practical debugging tool for the training of deep neural networks,

Reference 28

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Observation 6f96cfde-236e-4f0a-96ee-6bf6b7e6ca00 · outbound

This paper cites Ruishi Chen, Victor R Lee, Annie Camey Kuo, Denise Clark Pope, and Sarah Miles.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Ruishi Chen, Victor R Lee, Annie Camey Kuo, Denise Clark Pope, and Sarah Miles

Reference 29

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Observation a1531fee-371a-4f22-a6df-6977348e0687 · outbound

This paper cites A kernel two-sample test,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs A kernel two-sample test,

Reference 30

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Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Hidden technical debt in machine learning systems,

Reference 31

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This paper cites Automatically translating bug reports into test cases for mobile apps.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Automatically translating bug reports into test cases for mobile apps

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T04:48:59.755519Z

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Observation cad5aed3-d9a2-43b5-a9e4-2a1f0eb82225 · outbound

This paper cites Traceability transformed: Generating more accurate links with pre-trained BERT models.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Traceability transformed: Generating more accurate links with pre-trained BERT models

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T04:48:59.761204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9325fdd7-7e55-4fb6-bd9c-9c84fdada9f4 · outbound

This paper cites Detecting numerical bugs in neural network architectures,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Detecting numerical bugs in neural network architectures,

Reference 34

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Source-reported events for the cited work

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Observation a7619762-d39a-4e9b-bf09-aa60130923df · outbound

This paper cites In: Chandra, S., Blincoe, K., Tonella, P.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs In: Chandra, S., Blincoe, K., Tonella, P

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T04:48:59.717594Z

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Observation 8d8ecaa3-c1ce-4e6d-8489-48e8e14a7563 · outbound

This paper cites https://doi.org/10.1109/fg.2018.00021.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs https://doi.org/10.1109/fg.2018.00021

Reference 36

Resolution: malformed identifier; arxiv_id, observed 2026-07-04T13:59:52.024212Z

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Observation cb7c5a8c-4e26-4d5d-9299-4206e202723f · outbound

This paper cites An empirical study of the realism of mutants in deep learning,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs An empirical study of the realism of mutants in deep learning,

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:59:52.021424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 28966e13-1b08-45cb-b5e4-d638e3a46bb4 · outbound

This paper cites A comparative study to benchmark cross-project defect prediction approaches,.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs A comparative study to benchmark cross-project defect prediction approaches,

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-06-26T04:48:59.710389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 44ecb89d-f8e3-4d3d-89df-bab8e2a205f4 · outbound

This paper cites Parashar et al.

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs Parashar et al

Reference 39

Resolution: metadata mismatch; arxiv_id, observed 2026-06-26T04:48:59.732470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Pith citing papers

No inbound Pith citation observations are available.