Paper Citation Record · LEDGER

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair

As of 17 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2506.04987.

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

pith.paper-citation-record.v1
2506.04987 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:32:29.493622Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

42 of 42 outbound references displayed

verified exact6
verified fuzzy7
unresolved22
parse uncertain0
malformed identifier3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d6890629-cf98-402b-a9d4-7f4ecada1735 · outbound

This paper cites In: Cybersecurity Systems for Hu- man Cognition Augmentation, Advances in Information Security, vol.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: Cybersecurity Systems for Hu- man Cognition Augmentation, Advances in Information Security, vol

Reference 1

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Observation 304ce024-f97e-4375-bb20-6f07cf1137cd · outbound

This paper cites In: 2017 19th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC).

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: 2017 19th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

Reference 2

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This paper cites an unresolved cited work.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Unresolved cited work

Reference 3

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Observation 757b9147-251f-449f-829e-43b2f532cfea · outbound

This paper cites In: 2022 IEEE/ACM 19th International Conference on Mining Software Repositories (MSR).

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: 2022 IEEE/ACM 19th International Conference on Mining Software Repositories (MSR)

Reference 4

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Observation f4dd14c8-e08d-4fce-9714-21a8f34dc8b0 · outbound

This paper cites In: 8th USENIX Conference on Operating Systems Design and Implementation.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: 8th USENIX Conference on Operating Systems Design and Implementation

Reference 5

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Observation 992cd7df-3427-4eca-a7e4-8a3c6873e0fe · outbound

This paper cites https://doi.org/10.1109/TSE.2020.3020502.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair https://doi.org/10.1109/TSE.2020.3020502

Reference 6

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Observation 9c68eca1-22c5-4cba-b39b-48e47e3665a4 · outbound

This paper cites IEEE Transactions on Software Engineering47(09), 1943–1959 (September 2021).

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair IEEE Transactions on Software Engineering47(09), 1943–1959 (September 2021)

Reference 7

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Observation c1290e54-9595-44c5-adae-9bc5ec4e4429 · outbound

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A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Unresolved cited work

Reference 8

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Observation 6a3687fc-341c-4959-b676-6939f532b1b7 · outbound

This paper cites an unresolved cited work.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Unresolved cited work

Reference 9

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Observation 8a34fc7c-427f-439b-b849-ee915525920d · outbound

This paper cites In: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

Reference 10

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Source-reported events for the cited work

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Observation 2a960adf-d914-4006-8ea8-11d6a20ea3ea · outbound

This paper cites In: Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering

Reference 11

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Observation b7751e8c-8321-459d-ba51-6618a9a04bf3 · outbound

This paper cites CodeBERT: A Pre-Trained Model for Programming and Natural Languages.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Reference 12

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Observation 0b229d5b-ae88-4569-bf80-08d223f96b83 · outbound

This paper cites In: Findings of the Association for Computational Lin- guistics: EMNLP 2020.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: Findings of the Association for Computational Lin- guistics: EMNLP 2020

Reference 13

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Observation bbfbcca7-e0f3-48fa-9807-1a3e0f9bdb7e · outbound

This paper cites Learning from What We Know: How to Perform Vulnerability Prediction using Noisy Historical Data.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Learning from What We Know: How to Perform Vulnerability Prediction using Noisy Historical Data

Reference 14

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Observation 9f305d4e-4d5e-4e39-9ed0-5bf27ce5bdcd · outbound

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A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Unresolved cited work

Reference 15

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Source-reported events for the cited work

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Observation 168f2c92-13d1-4df4-a097-15155b7365b7 · outbound

This paper cites Vulnerability Mimicking Mutants.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Vulnerability Mimicking Mutants

Reference 16

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Observation c60109ea-cfb1-4203-b1e0-12a71ba1caa4 · outbound

This paper cites In: IEEE Con- ference on Software Testing, Verification and Validation, ICST 2024, Toronto, ON, Canada, May 27-31, 2024.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: IEEE Con- ference on Software Testing, Verification and Validation, ICST 2024, Toronto, ON, Canada, May 27-31, 2024

Reference 17

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Observation 9d63b4b5-11e5-40e0-a01b-110f1d1fb26c · outbound

This paper cites techrxiv preprint (Dec 2024).https:// doi.org/10.36227/techrxiv.173385946.65994728/v1, http://dx.doi.org/10.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair techrxiv preprint (Dec 2024).https:// doi.org/10.36227/techrxiv.173385946.65994728/v1, http://dx.doi.org/10

Reference 18

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Observation b67bd666-a5ca-480a-ba12-f3a2d22fb7dd · outbound

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A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Unresolved cited work

Reference 19

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Observation 2e90c6f1-ad5b-4f8a-ac5e-9ec7a5247671 · outbound

This paper cites Commu- nications of the ACM62(12), 56–65 (2019).https://doi.org/10.1145/3318162.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Commu- nications of the ACM62(12), 56–65 (2019).https://doi.org/10.1145/3318162

Reference 20

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Observation 1462d5a7-f83f-45e7-ad4a-d35524ef34d5 · outbound

This paper cites In: 9th International Conference on Learning Representa- tions, ICLR 2021, Virtual Event, Austria, May 3-7, 2021.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: 9th International Conference on Learning Representa- tions, ICLR 2021, Virtual Event, Austria, May 3-7, 2021

Reference 21

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Observation 0fd29298-0dfa-465a-aace-bd4aa937a90e · outbound

This paper cites In: European Symposium on Research in Computer Security.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: European Symposium on Research in Computer Security

Reference 22

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Observation 200a7787-ce70-4211-95b0-dbcad5ba593c · outbound

This paper cites In: Guide to Vulnerability Analysis for Com- puter Networks and Systems - An Artificial Intelligence Approach, pp.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: Guide to Vulnerability Analysis for Com- puter Networks and Systems - An Artificial Intelligence Approach, pp

Reference 23

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Observation 2b1d4b5c-fcbf-4021-813a-910ff9d75061 · outbound

This paper cites 15599983.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair 15599983

Reference 24

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This paper cites In: 44th IEEE/ACM 44th International Conference on Software Engineering, ICSE 2022, Pittsburgh, PA, USA, May 25-27, 2022.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: 44th IEEE/ACM 44th International Conference on Software Engineering, ICSE 2022, Pittsburgh, PA, USA, May 25-27, 2022

Reference 25

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Observation b8ac64bc-2ea5-48d9-88f4-1cd102366be3 · outbound

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Reference 26

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A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: 34th In- ternational Conference on Software Engineering (ICSE)

Reference 28

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A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: Proceedings of the 28th ACM SIGSOFT Interna- tional Symposium on Software Testing and Analysis

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A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: 38th International Conference on Software Engineering (ICSE)

Reference 30

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A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: 35th International Conference on Software Engineering (ICSE)

Reference 31

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A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: Proceedings of the 21st In- ternational Conference on Mining Software Repositories

Reference 32

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Reference 33

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Observation 85801428-8275-4fbe-8028-9b19599db5f1 · outbound

This paper cites IEEE Trans.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair IEEE Trans

Reference 34

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A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: Proceedings of the 40th annual meeting of the Association for Computational Linguistics

Reference 35

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Observation 761b3c6d-9d4d-48f3-8e76-858c36326abf · outbound

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Reference 36

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This paper cites CodeBLEU: a Method for Automatic Evaluation of Code Synthesis.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair CodeBLEU: a Method for Automatic Evaluation of Code Synthesis

Reference 37

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This paper cites In: 33rd USENIX Security Symposium, USENIX Security 2024, Philadelphia, PA, USA, August 14-16, 2024.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: 33rd USENIX Security Symposium, USENIX Security 2024, Philadelphia, PA, USA, August 14-16, 2024

Reference 38

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Observation 49f27ff5-6d56-4847-ab59-693e824f8fd8 · outbound

This paper cites CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

Reference 39

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This paper cites In: Proceedings of the 32nd ACM SIGSOFT International Symposium on Soft- ware Testing and Analysis, ISSTA 2023, Seattle, WA, USA, July 17-21, 2023.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: Proceedings of the 32nd ACM SIGSOFT International Symposium on Soft- ware Testing and Analysis, ISSTA 2023, Seattle, WA, USA, July 17-21, 2023

Reference 40

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Observation 66c26b7f-3ccf-444e-a530-db7d0ca5d3d2 · outbound

This paper cites IEEE Transactions on Software Engineering 43, 34–55 (2017).

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair IEEE Transactions on Software Engineering 43, 34–55 (2017)

Reference 41

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Observation 3e57926f-9588-41eb-ab7e-853eaab6c41a · outbound

This paper cites IEEE Access 8, 166335–166346 (2020).

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair IEEE Access 8, 166335–166346 (2020)

Reference 42

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This paper cites https://doi.org/10.1007/978-3-319-10374-7_3 , https: //doi.org/10.1007/978-3-319-10374-7_3.

A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair https://doi.org/10.1007/978-3-319-10374-7_3 , https: //doi.org/10.1007/978-3-319-10374-7_3

Reference 60

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Pith citing papers

No inbound Pith citation observations are available.