Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:32:29.493622Z
Paper Citation Record · LEDGER
As of 8 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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:32:29.493622Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
42 of 42 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation d6890629-cf98-402b-a9d4-7f4ecada1735 · outbound
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: Cybersecurity Systems for Hu- man Cognition Augmentation, Advances in Information Security, vol
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Observation 304ce024-f97e-4375-bb20-6f07cf1137cd · outbound
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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Observation caf17d2d-cc27-44da-9ca7-c2f3e131103e · outbound
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
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
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
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
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair IEEE Transactions on Software Engineering47(09), 1943–1959 (September 2021)
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Observation c1290e54-9595-44c5-adae-9bc5ec4e4429 · outbound
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Observation 6a3687fc-341c-4959-b676-6939f532b1b7 · outbound
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
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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Observation 2a960adf-d914-4006-8ea8-11d6a20ea3ea · outbound
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
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
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
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
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Unresolved cited work
Reference 15
Source-reported events for the cited work
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Observation 168f2c92-13d1-4df4-a097-15155b7365b7 · outbound
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
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
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
Source-reported events for the cited work
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Observation b67bd666-a5ca-480a-ba12-f3a2d22fb7dd · outbound
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Unresolved cited work
Reference 19
Source-reported events for the cited work
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Observation 2e90c6f1-ad5b-4f8a-ac5e-9ec7a5247671 · outbound
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
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
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
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
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair 15599983
Reference 24
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Observation 4b55a652-353d-4853-89dc-e34e872a8ba9 · outbound
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
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Unresolved cited work
Reference 26
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Observation f8e81667-1ad1-4cbd-aa1b-734e75448c15 · outbound
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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Observation d2f800b2-84bf-4e9f-9744-e4d473e64bfb · outbound
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
Reference 29
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Observation 9df88073-9097-4a94-a638-0e58b69e75d9 · outbound
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: 38th International Conference on Software Engineering (ICSE)
Reference 30
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Observation 0025a95c-2a3c-4098-9924-02fd555d602c · outbound
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair In: 35th International Conference on Software Engineering (ICSE)
Reference 31
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Observation be8fa163-cd32-4e10-9458-041230cc7c5e · outbound
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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Observation 4ee20d68-5d53-4807-ba69-54a4a8e25855 · outbound
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Unresolved cited work
Reference 33
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Observation 85801428-8275-4fbe-8028-9b19599db5f1 · outbound
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair IEEE Trans
Reference 34
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Observation 9f2969c7-9db3-475b-86d3-a51dd6efac3a · outbound
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
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair Unresolved cited work
Reference 36
Source-reported events for the cited work
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Observation 6e933980-5603-49db-b319-bc4e42eff9b8 · outbound
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair CodeBLEU: a Method for Automatic Evaluation of Code Synthesis
Reference 37
Source-reported events for the cited work
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Observation 7bccbdd3-2669-42d9-b701-60d3a938a64e · outbound
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
Source-reported events for the cited work
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Observation 49f27ff5-6d56-4847-ab59-693e824f8fd8 · outbound
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
Source-reported events for the cited work
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Observation 3b484133-1181-4cab-ac35-3591a5552bea · outbound
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
Source-reported events for the cited work
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Observation 66c26b7f-3ccf-444e-a530-db7d0ca5d3d2 · outbound
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair IEEE Transactions on Software Engineering 43, 34–55 (2017)
Reference 41
Source-reported events for the cited work
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Observation 3e57926f-9588-41eb-ab7e-853eaab6c41a · outbound
A Multi-Dataset Evaluation of Models for Automated Vulnerability Repair IEEE Access 8, 166335–166346 (2020)
Reference 42
Source-reported events for the cited work
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Observation 3c71f3e4-bce5-4ce9-9feb-9db6bb8ec8a1 · outbound
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
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.
No inbound Pith citation observations are available.