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Paper Citation Record · LEDGER

Empirical Evaluation of Large Language Models in Automated Program Repair

As of 9 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 2 inbound Pith citation observations for arXiv:2506.13186.

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

pith.paper-citation-record.v1
2506.13186 v1

Coverage vector

measured 79 of 79 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:42:05.472880Z

measured 81 of 81 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T15:06:55.050376Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T05:57:24.432794Z

Reference resolution

79 of 79 outbound references displayed

  • verified exact0
  • verified fuzzy56
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b167f023-3aeb-4ead-87bb-3be516ef7ee1 · outbound

This paper cites The debugging mindset: Understanding the psychology of learning strategies leads to effective problem-solving skills.

Empirical Evaluation of Large Language Models in Automated Program Repair The debugging mindset: Understanding the psychology of learning strategies leads to effective problem-solving skills

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.240703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:41:59.444522Z digest=sha256:caa19673c11ea994fff383e8364ca90f934a750c269d6480778aa3f9f5d1a1ec

Observation b0258e0a-e192-4a1c-8c68-00beae8a946a · outbound

This paper cites Genprog: A generic method for automatic software repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Genprog: A generic method for automatic software repair,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.230666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:41:59.501952Z digest=sha256:b9795d9b53a12c8ed0de19556ce72a7ac1f65452863ab75749fe12f447ba19d4

Observation fec9e93c-374f-43be-ab4d-ccb6c5fdc2b6 · outbound

This paper cites Nopol: Automatic repair of conditional statement bugs in java programs,.

Empirical Evaluation of Large Language Models in Automated Program Repair Nopol: Automatic repair of conditional statement bugs in java programs,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.221383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:41:59.555989Z digest=sha256:292ceb406126d436191c0c74af5dba0d1380a2cefd4a3d5e081a8dcc6fb5229a

Observation 1be5c364-e6c2-4dd1-9dff-5d0d56b98bf4 · outbound

This paper cites S3: syntax- and semantic-guided repair synthesis via programming by examples,.

Empirical Evaluation of Large Language Models in Automated Program Repair S3: syntax- and semantic-guided repair synthesis via programming by examples,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.211545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:41:59.663118Z digest=sha256:3b69b8d59881d59aeb45e218fa27547439289f5022b0405b9e0393aa92d38469

Observation f3684160-823d-471d-aabd-bf85a36a4d0c · outbound

This paper cites Staged program repair with condition synthesis,.

Empirical Evaluation of Large Language Models in Automated Program Repair Staged program repair with condition synthesis,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.202384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:41:59.728744Z digest=sha256:761c7641d6bb02e79526aa6265329a3406b2144259394f43ca1516fe29cfd93b

Observation e5142586-429b-4d87-8f3b-e8613068e4c7 · outbound

This paper cites Angelix: Scalable multiline program patch synthesis via symbolic analysis,.

Empirical Evaluation of Large Language Models in Automated Program Repair Angelix: Scalable multiline program patch synthesis via symbolic analysis,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.192887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:41:59.800504Z digest=sha256:31bd911ad5e8e6d440e377ee0cf3913ea013615318959b5835ae300af6f7a92d

Observation 12bfc4d2-6a0e-4392-9338-213d63a946a7 · outbound

This paper cites Astor: A program repair library for java,.

Empirical Evaluation of Large Language Models in Automated Program Repair Astor: A program repair library for java,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.183114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:41:59.850334Z digest=sha256:1257f202cfc0dd2c8dead59438ad96039886d59e8ed3cd058f642a7848e38075

Observation dcbd5c05-4553-4527-a135-7da6f642e4f1 · outbound

This paper cites History driven program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair History driven program repair,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.173408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:41:59.908963Z digest=sha256:f015933a6536140a220e0dcbe17aa324b4ccea2c7fc90550c3dc9ef3d140c246

Observation d4f33bc5-e716-4ef2-a8db-f104b7270513 · outbound

This paper cites Automatic patch generation by learning correct code,.

Empirical Evaluation of Large Language Models in Automated Program Repair Automatic patch generation by learning correct code,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.163121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:41:59.998933Z digest=sha256:bb13c075fba5d250681d07233aa6185bab0a8e7b7fcf5c12e1f79688959f2d63

Observation a82ae89a-5d64-4f65-8722-3a611339bd54 · outbound

This paper cites Leveraging syntax-related code for automated program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Leveraging syntax-related code for automated program repair,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.152650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.044997Z digest=sha256:9d7c79b8267c61c554366005113595e074e412f58d7d2346ffed692c26882947

Observation 1a9e125e-47fc-43ad-9b21-e394ad4819b3 · outbound

This paper cites Precise condition synthesis for program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Precise condition synthesis for program repair,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.143327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.134660Z digest=sha256:7ee936b2c38aadc536b1a65f9a6c351e60fa1da62a7232c16156cda248419787

Observation 8daf1de8-8a74-4f81-8fd6-cd5eb1935dc9 · outbound

This paper cites Automatic inference of code transforms for patch generation,.

Empirical Evaluation of Large Language Models in Automated Program Repair Automatic inference of code transforms for patch generation,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.133299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.179038Z digest=sha256:74db36c4d5e6aa46917b08b8336c0ef304c9c906f3899da2a654d5154ebac9cb

Observation a91899b0-3bc4-4ce6-bf47-fa49b316d55d · outbound

This paper cites Towards practical program repair with on-demand candidate generation,.

Empirical Evaluation of Large Language Models in Automated Program Repair Towards practical program repair with on-demand candidate generation,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.124032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.235932Z digest=sha256:51708de8c9c22c48a8ff3fa94c9c9d83db7aec6e4c8bc44024d82fdff9e01f64

Observation 2419a248-dd07-4c16-9866-400c3d19ee80 · outbound

This paper cites Context-aware patch generation for better automated program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Context-aware patch generation for better automated program repair,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.114649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.296258Z digest=sha256:91f446c174100d62571abda37410903c3400ffe0718454ebd85943d18270a881

Observation 14cee7f8-6e84-4240-8655-7ae6d43ef020 · outbound

This paper cites Shaping program repair space with existing patches and similar code,.

Empirical Evaluation of Large Language Models in Automated Program Repair Shaping program repair space with existing patches and similar code,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.105045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.355358Z digest=sha256:04ec7ec5128a9950bbd2ad21fc640464bcac56e1df8f14cfb1d98d8df7ffd4a3

Observation eab405de-641b-47f9-8578-f29250fee8fc · outbound

This paper cites Tbar: Revisiting template-based automated program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Tbar: Revisiting template-based automated program repair,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.095272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.412296Z digest=sha256:8781b80ff292e87e3d35d38cc09275984428b6829d39aec1b433bb62a8ef44ae

Observation df8f5b3c-5fdc-460c-a4b8-91ddb4702f95 · outbound

This paper cites Avatar: Fixing semantic bugs with fix patterns of static analysis violations,.

Empirical Evaluation of Large Language Models in Automated Program Repair Avatar: Fixing semantic bugs with fix patterns of static analysis violations,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.085697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.508136Z digest=sha256:fe622bc5c40a700affa3de16fd2b90c7903e14fd708171efbd8f4a221ea6c035

Observation 824fb81a-f85f-4cdd-be5d-7612145a97ea · outbound

This paper cites Practical program repair via bytecode mutation,.

Empirical Evaluation of Large Language Models in Automated Program Repair Practical program repair via bytecode mutation,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.075497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.563390Z digest=sha256:e30ea5d834dc1fe6d6da2a0ff95e33bc7b707fb9a47581d8dc0fa6c56fe3c299

Observation 40a98f43-ce8c-4078-a88a-9c3e76c300d4 · outbound

This paper cites Inferring program transfor- mations from singular examples via big code,.

Empirical Evaluation of Large Language Models in Automated Program Repair Inferring program transfor- mations from singular examples via big code,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.064987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.614514Z digest=sha256:1fcdfcf3f38ae51fc1f4435f99290468ff857a393547cce152bed5c7d67d106d

Observation 6e5ff99e-aa98-4872-9f3d-93c009ec6061 · outbound

This paper cites The plastic surgery hypothesis in the era of large language models,.

Empirical Evaluation of Large Language Models in Automated Program Repair The plastic surgery hypothesis in the era of large language models,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.055015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.669053Z digest=sha256:522520b14e59baf083a3ed40809dc1a8d3c8156c233a6373f11c91ee120c54db

Observation 76c5b301-c4e8-4f53-b2ca-f42df3cd92d7 · outbound

This paper cites Sequencer: Sequence-to-sequence learning for end- to-end program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Sequencer: Sequence-to-sequence learning for end- to-end program repair,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.044297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.722403Z digest=sha256:63a59630c7b306c3dd2feeaeec20cdc5ae362e9c27da3b41de36dc0bf0af2dd7

Observation 20d6c679-fdae-4ccb-854e-c531c40ebe60 · outbound

This paper cites Coconut: combining context-aware neural translation models using ensemble for program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Coconut: combining context-aware neural translation models using ensemble for program repair,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.035055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.775241Z digest=sha256:4849e20481a69554a2e684b418f6e5c6de302b48a6a0d413cd70e831b6b37055

Observation 83986091-dad1-4b05-8a6e-9e7f4ee67b54 · outbound

This paper cites Dlfix: Context-based code transformation learning for automated program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Dlfix: Context-based code transformation learning for automated program repair,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.025782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.856107Z digest=sha256:8f976d86ca4e738d61b785601d37ff5a19004dbccd8b89b411f70f97c25bdf01

Observation e6de4167-2e91-408d-a26e-4926315cfdb1 · outbound

This paper cites A syntax-guided edit decoder for neural program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair A syntax-guided edit decoder for neural program repair,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.016369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.924694Z digest=sha256:4553c6a984b42df34d5f57d60e628e0a2798e0250c43f76859ba51f59ac17d86

Observation 8796f69d-9ee4-44d4-bb53-ffaca7f768e3 · outbound

This paper cites Cure: Code-aware neural machine translation for automatic program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Cure: Code-aware neural machine translation for automatic program repair,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:06.005991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:00.976528Z digest=sha256:b0b0f410b0c2ee5ba5700562f05a2e1539d6381108dd62381d3dddba2d0ac6bf

Observation be5ffd9d-7362-4a38-95c6-0f8edb534c66 · outbound

This paper cites Neural program repair with execution-based backpropagation,.

Empirical Evaluation of Large Language Models in Automated Program Repair Neural program repair with execution-based backpropagation,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.995572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:01.051254Z digest=sha256:34af9981efc33ebc4f7fa20b0e1f6788977a236f790d41e4cb70c3b92f7f108c

Observation eb43304e-50c7-41e2-a187-5ca3ef30ac27 · outbound

This paper cites Tare: Type-aware neural program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Tare: Type-aware neural program repair,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.984769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:01.187004Z digest=sha256:9f43403271d2a2cfdf930fd5c894806d4d4f90f958d362107eb228c5f1b15add

Observation 39adb762-c39f-4fb0-8f79-b49f7e1bc8df · outbound

This paper cites Vulrepair: a t5-based automated software vulnerability repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Vulrepair: a t5-based automated software vulnerability repair,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.975049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:01.293848Z digest=sha256:962112b4a7687cbe905f3ab21f4b39d0fac03b6c25320e505695c2f3b877daba

Observation 45ed4b8a-9196-4c11-93e4-7d97271e9cf8 · outbound

This paper cites Less training, more repairing please: revisiting automated program repair via zero-shot learning,.

Empirical Evaluation of Large Language Models in Automated Program Repair Less training, more repairing please: revisiting automated program repair via zero-shot learning,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.964939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:01.341834Z digest=sha256:08dbf4b098b7d13201471dc915762046fa37e0a0f6a624cfd47eda38222b2976

Observation bd9d3dd8-2e81-4187-a3f6-eadb708e6b81 · outbound

This paper cites Prompting is all you need: Automated android bug replay with large language models,.

Empirical Evaluation of Large Language Models in Automated Program Repair Prompting is all you need: Automated android bug replay with large language models,

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:01.431179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:01.431179Z digest=sha256:815de08eb5710faa44a2a4000395c6b22d65e786858d98e3c43f53f8ff1af07a

Observation f30c9134-5bde-46a6-83ae-1f22e9b1e495 · outbound

This paper cites UniXcoder: Unified Cross-Modal Pre-training for Code Representation.

Empirical Evaluation of Large Language Models in Automated Program Repair UniXcoder: Unified Cross-Modal Pre-training for Code Representation

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:01.663531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:01.663531Z digest=sha256:acfd2ca4d23e693e4ea8603332f2a198dcaca04acd6f45995c22485936da855a

Observation 87540288-3fae-4b86-ad57-5ffbc7223095 · outbound

This paper cites CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis.

Empirical Evaluation of Large Language Models in Automated Program Repair CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:01.795662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:01.795662Z digest=sha256:ec3e6a9616a280b19eedbd4b613e901af24691733beff7b3b3318554e53148f3

Observation 72d2a4e6-3669-4d0b-8395-a636b64f53b1 · outbound

This paper cites CodeT5+: Open Code Large Language Models for Code Understanding and Generation.

Empirical Evaluation of Large Language Models in Automated Program Repair CodeT5+: Open Code Large Language Models for Code Understanding and Generation

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:01.938924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:01.938924Z digest=sha256:bd65143e91947540d9ef2c0356781b00dfe4a39758db5191a9e50f097cfb3c7e

Observation a14e427d-ca39-4cc4-aa8d-5d032d4c6a55 · outbound

This paper cites Few-shot training llms for project-specific code-summarization,.

Empirical Evaluation of Large Language Models in Automated Program Repair Few-shot training llms for project-specific code-summarization,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.948557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:02.070297Z digest=sha256:1ddf82767477ffe69ffce97766666592dc734fec41c88a4e805608e6407418a8

Observation 11988c79-de0a-4047-b547-158d6c01a4cf · outbound

This paper cites Can openai’s codex fix bugs? an evaluation on quixbugs,.

Empirical Evaluation of Large Language Models in Automated Program Repair Can openai’s codex fix bugs? an evaluation on quixbugs,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.938979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:02.236582Z digest=sha256:6ef6bd75552cb63d0eeb0e5cb63c9829f9b92b0a2af2945c223b978bfc8812b2

Observation 71212d70-bae2-4a25-a985-2dae3756a3e8 · outbound

This paper cites Impact of code language models on automated program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Impact of code language models on automated program repair,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.929747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:02.352819Z digest=sha256:ae8def8b678b4227713b92aea70b4273f1a786dd28187a677b3bc90f92b7856e

Observation a5dc196a-4e68-4f5f-b48d-92ac96460765 · outbound

This paper cites Automated program repair in the era of large pre-trained language models,.

Empirical Evaluation of Large Language Models in Automated Program Repair Automated program repair in the era of large pre-trained language models,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.920026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:02.553542Z digest=sha256:158bc5121c8b0c2818b233c470b86061f170ff5ed531d304e85e3f0c7724b733

Observation b6741863-1deb-43b7-90ac-7eb0d1fbccaa · outbound

This paper cites Automated repair of programs from large language models,.

Empirical Evaluation of Large Language Models in Automated Program Repair Automated repair of programs from large language models,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.909849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:02.700004Z digest=sha256:e8dd0b469fc98fb79374cd556d7f38045701d850b6e022610a8437c102761a2b

Observation 96adef9e-365e-494a-b863-4b0c845df6ea · outbound

This paper cites Gamma: Revisiting template-based automated program repair via mask prediction,.

Empirical Evaluation of Large Language Models in Automated Program Repair Gamma: Revisiting template-based automated program repair via mask prediction,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.899311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:02.816392Z digest=sha256:2b7974f1280b14850cc5b5f8fdf2cc6d129ffb53cb2f0e1ac9bf668a1eb72e86

Observation ce07b5f5-d85c-4cb4-8702-e0107a8877f3 · outbound

This paper cites Thinkrepair: Self-directed automated program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Thinkrepair: Self-directed automated program repair,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.888905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:02.981678Z digest=sha256:f247380409a0815306ea153f2849b76718915532586c31b940f0c0918d689508

Observation d77097f1-f099-446a-84a6-34e63dfd4890 · outbound

This paper cites Keep the Conversation Going: Fixing 162 out of 337 bugs for $0.42 each using ChatGPT.

Empirical Evaluation of Large Language Models in Automated Program Repair Keep the Conversation Going: Fixing 162 out of 337 bugs for $0.42 each using ChatGPT

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:03.138296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:03.138296Z digest=sha256:196cb42c02f277cc7db82ea4392b13890429ee7b58c0beeab7eb582483db5547

Observation 98fd2f8f-62b1-4077-a1e6-4354f99d6d4e · outbound

This paper cites An empirical study on fine-tuning large language models of code for automated program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair An empirical study on fine-tuning large language models of code for automated program repair,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.879214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:03.322281Z digest=sha256:3183983b3966b6e25f7afef519fc4699c7d1101b7cd5a0829ef4ab73906eb6c4

Observation 21468d90-0805-48e3-aec4-fca00d321f3b · outbound

This paper cites How Far Can We Go with Practical Function-Level Program Repair?.

Empirical Evaluation of Large Language Models in Automated Program Repair How Far Can We Go with Practical Function-Level Program Repair?

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:03.480214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:03.480214Z digest=sha256:f35e462f257d07dca7cf39dbe07629f23927cd0c10c9d17573f0d674eac08fbe

Observation b0f7b167-a413-410c-ad5b-17c321a70e03 · outbound

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

Empirical Evaluation of Large Language Models in Automated Program Repair CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:03.627340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:03.627340Z digest=sha256:c1cc2a458e5f45857c3a5f7ad62cc309c8aefd4f947f3fae7859d88368f8e98c

Observation 1afb6817-ed90-44b2-8915-55e1e791a7f3 · outbound

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

Empirical Evaluation of Large Language Models in Automated Program Repair CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

Reference 45

Resolution
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no resolver link, observed 2026-08-07T00:42:03.731652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:03.731652Z digest=sha256:33af4e475545284b56185ed173d436e2966710ef6887de3957ee72b781681567

Observation 758c4715-52aa-4cd4-8b03-1727af3945f7 · outbound

This paper cites Defects4j: A database of existing faults to enable controlled testing studies for java programs,.

Empirical Evaluation of Large Language Models in Automated Program Repair Defects4j: A database of existing faults to enable controlled testing studies for java programs,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.868542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:03.832274Z digest=sha256:3f18abef722881190ab196e65fe4a2657152d0de25820dd992a9ca2bf97420c0

Observation c1fc1f57-f631-4ef0-b5f2-d8b7186e9d57 · outbound

This paper cites The manybugs and introclass benchmarks for automated repair of c programs,.

Empirical Evaluation of Large Language Models in Automated Program Repair The manybugs and introclass benchmarks for automated repair of c programs,

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:03.902785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:03.902785Z digest=sha256:281a2004864698fcc8e02b51ce4a4b264b3e32a847cf25e754617cb1e12bdc14

Observation 26afc1d8-52b2-4708-8300-61f244381d91 · outbound

This paper cites Quixbugs: A multi- lingual program repair benchmark set based on the quixey challenge,.

Empirical Evaluation of Large Language Models in Automated Program Repair Quixbugs: A multi- lingual program repair benchmark set based on the quixey challenge,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.853231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:04.032946Z digest=sha256:20c284820d252f71516992a51f2a5231e360d34e05d555e6abf5fb7ead283cae

Observation 49dfc44b-32a7-4799-bdc1-6ade43900b54 · outbound

This paper cites An overview of large ai models and their applications,.

Empirical Evaluation of Large Language Models in Automated Program Repair An overview of large ai models and their applications,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.844090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:04.114251Z digest=sha256:a705a661ec7790c5fc8072e7ac990553e1e089a113c695c4f3b01bb0157b8766

Observation f8eff1b3-e612-4aba-8e72-316a59496d27 · outbound

This paper cites The Cost of Training NLP Models: A Concise Overview.

Empirical Evaluation of Large Language Models in Automated Program Repair The Cost of Training NLP Models: A Concise Overview

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:04.244106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:04.244106Z digest=sha256:89731c07a20cea846ec487ff1eefbc3e70fc5d6a82c7a409e990539dc44528d7

Observation f86b1894-1265-47fa-8cb9-f80bd7d7d7b4 · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Empirical Evaluation of Large Language Models in Automated Program Repair Code Llama: Open Foundation Models for Code

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:04.329887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:04.329887Z digest=sha256:d46fbbe4be161eb3f521ae0759eee3e583975d75004f973eef9ba7cfab131324

Observation 7accd6b2-a4e5-4940-b73c-383e0f4eeffc · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Empirical Evaluation of Large Language Models in Automated Program Repair Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:04.420135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:04.420135Z digest=sha256:aa9ec67bb8eccb4748e8e075ccb298cdabd15c37cb0ee9dc299f9ab287ac1ebb

Observation 24a46f90-1e97-467e-88ba-1ade845c20f6 · outbound

This paper cites StarCoder: may the source be with you!.

Empirical Evaluation of Large Language Models in Automated Program Repair StarCoder: may the source be with you!

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:04.536895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:04.536895Z digest=sha256:777ca090fd9e987f12867c84ab8d2a1fcc26805f6135f5f46ddf50aa50979438

Observation 72fb79e8-f04b-431e-a3ca-aa36c8637845 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Empirical Evaluation of Large Language Models in Automated Program Repair DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:04.649827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:04.649827Z digest=sha256:08862ef7e79541e8693cb71d871b60aad9173182bdc87a140b3564dddad88b8d

Observation 7f35cd4c-3c94-4e94-94f1-96e2ebdd80f4 · outbound

This paper cites Bugsc++: A highly usable real world defect benchmark for c/c++,.

Empirical Evaluation of Large Language Models in Automated Program Repair Bugsc++: A highly usable real world defect benchmark for c/c++,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.834621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:04.737314Z digest=sha256:c5fd5a07437fe17eb72a610afbf6895fefaafa3a9857220a71dc1071dd751550

Observation 16bcf1d0-f2e3-4c55-9c95-50eea4e4a965 · outbound

This paper cites Introclassjava: A benchmark of 297 small and buggy java programs,.

Empirical Evaluation of Large Language Models in Automated Program Repair Introclassjava: A benchmark of 297 small and buggy java programs,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.825380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:04.810975Z digest=sha256:4222b98086134588b13af166c5a025be78617f143a296fbec419b3c5b6c9cd72

Observation 85559a4d-8504-45af-a6eb-cbf78c345fe6 · outbound

This paper cites ConDefects: A New Dataset to Address the Data Leakage Concern for LLM-based Fault Localization and Program Repair.

Empirical Evaluation of Large Language Models in Automated Program Repair ConDefects: A New Dataset to Address the Data Leakage Concern for LLM-based Fault Localization and Program Repair

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:04.948194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:04.948194Z digest=sha256:51e42dae56d26c3d7620148e794c3747ce058ea13b1840cd665ca0df7402b4f8

Observation 8b11fc15-23a8-40b4-a76a-184428472385 · outbound

This paper cites Attention is all you need,.

Empirical Evaluation of Large Language Models in Automated Program Repair Attention is all you need,

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:05.051611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:05.051611Z digest=sha256:e5cf9f6552f8bd762854191b390d3cbe80c3f57752d3ce408625024f82e1a666

Observation 94df2463-7a28-411c-816f-51d15f78510f · outbound

This paper cites Scaling Laws for Neural Language Models.

Empirical Evaluation of Large Language Models in Automated Program Repair Scaling Laws for Neural Language Models

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:05.171629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:05.171629Z digest=sha256:56b77046e30bdc67d482b864bf4705eec080abbc4b6766878516536b4fd1c478

Observation 20d51a2a-2b9f-41d1-a7e5-9320708393e1 · outbound

This paper cites How to fine-tune bert for text classification?.

Empirical Evaluation of Large Language Models in Automated Program Repair How to fine-tune bert for text classification?

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.809993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.216894Z digest=sha256:c91823a6be3434358dee66fdc2be6857a4331ee295c80e4fcf0d78bae525670e

Observation 395ba91c-dd99-45f1-a74b-ac54d3b2a4a9 · outbound

This paper cites Parameter-efficient fine-tuning of large-scale pre-trained language models,.

Empirical Evaluation of Large Language Models in Automated Program Repair Parameter-efficient fine-tuning of large-scale pre-trained language models,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.800845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.248130Z digest=sha256:fa04d9f6a965146c63edc1a9f75a11573e1b67254d2e06fe955d207e5117b1e1

Observation 6a83e52f-062a-4de2-a231-7cfe1cd31a74 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

Empirical Evaluation of Large Language Models in Automated Program Repair The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:05.362416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:05.362416Z digest=sha256:a3fb0580ef0ba6d07647cdebf0c74929179086bd69a9653a2164b462980e73a5

Observation 6fb7979d-aa5e-4487-87df-695dc7e371e8 · outbound

This paper cites Visual prompt tuning,.

Empirical Evaluation of Large Language Models in Automated Program Repair Visual prompt tuning,

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:05.421426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:05.421426Z digest=sha256:689a7f69ddbc31872ffdb95920493c9df4bbd4cd8565d46e4b4f00d689230580

Observation 5b3dc69d-4f59-42dd-94e0-98c7e9cde194 · outbound

This paper cites RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair.

Empirical Evaluation of Large Language Models in Automated Program Repair RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:05.424919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:05.424919Z digest=sha256:c8696c0eee58223194a8132d65c3d95c6f5564c21fa2eb1a07bda2c934cf1224

Observation 0e006f2e-67e4-42de-9531-2a63aae568e5 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Empirical Evaluation of Large Language Models in Automated Program Repair Lora: Low-rank adaptation of large language models

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:05.428384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:05.428384Z digest=sha256:089b21558399357583cc85eaba8c2cce6a36afaec55969c0c0d56c0a2d026d07

Observation 0aa587ea-34f5-40c7-ad32-a661661efd1d · outbound

This paper cites Language models are few-shot learners,.

Empirical Evaluation of Large Language Models in Automated Program Repair Language models are few-shot learners,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.778200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.431659Z digest=sha256:c6958868a3b3b9cd1500062ebc78d917bcdd0c7627e0c2b6b20dfc6611aac515

Observation a15d5cee-f17f-48b3-a7f5-87d85476bd06 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Empirical Evaluation of Large Language Models in Automated Program Repair Chain-of-thought prompting elicits reasoning in large language models,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.768606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.435339Z digest=sha256:d1a094a4535010c02c705368ac69ac6e5d83289f2889436e3b180a8533cc229b

Observation 7e50a810-d84d-4cd0-8eb6-d0b0ab34c358 · outbound

This paper cites Automatic Chain of Thought Prompting in Large Language Models.

Empirical Evaluation of Large Language Models in Automated Program Repair Automatic Chain of Thought Prompting in Large Language Models

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:05.441867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:05.441867Z digest=sha256:e8449ea82d1ba8ff9c0f79d2ea8a724cb765b2379c50132b3a9e989ba6ee7be0

Observation b6094612-9c13-4d54-b8cd-ceddc3b278a3 · outbound

This paper cites Towards understanding chain-of-thought prompting: An empirical study of what matters,.

Empirical Evaluation of Large Language Models in Automated Program Repair Towards understanding chain-of-thought prompting: An empirical study of what matters,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.750080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.445261Z digest=sha256:104babcc4e89751e0b291548ce19327dcea8ec2bf93eaf7ac7ec8e746e9e81a2

Observation ad81bf8e-c8f9-48a0-ba15-8930e9b2725f · outbound

This paper cites Copiloting the copilots: Fusing large language models with completion engines for automated program repair,.

Empirical Evaluation of Large Language Models in Automated Program Repair Copiloting the copilots: Fusing large language models with completion engines for automated program repair,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.740858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.447945Z digest=sha256:0bbe64ac93163053482f11ae0390d789a41321d7a87cca94dd89fd83356690dd

Observation cc987921-c713-4283-8f42-bf026044ea93 · outbound

This paper cites Language models are few-shot learners,.

Empirical Evaluation of Large Language Models in Automated Program Repair Language models are few-shot learners,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.730831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.451148Z digest=sha256:6b9ff0d2f0e1cb90c7fe9d4ece77a668287dd4e73c33b17eec1aebfc3672ae82

Observation e44f86b7-e733-4626-839b-b8b9fde34cc9 · outbound

This paper cites Hybrid automated program repair by combining large language models and program analysis,.

Empirical Evaluation of Large Language Models in Automated Program Repair Hybrid automated program repair by combining large language models and program analysis,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.715419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.457284Z digest=sha256:8ec1f3c8b4f3fc3c3699fe077a1ab6e0be9492a9efbe6306c775c8fc7a11ba01

Observation a3686d76-ead4-4241-b460-ee9eebcd86b5 · outbound

This paper cites Atcoder,.

Empirical Evaluation of Large Language Models in Automated Program Repair Atcoder,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.703761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.460165Z digest=sha256:3210e8740103f7fe4046890eb239dfbef61c66a59e7847da79dce9dbc5023b84

Observation 55508178-2240-479c-b518-8719019d69cd · outbound

This paper cites Benchmarking automated program repair: An extensive study on both real-world and artificial bugs,.

Empirical Evaluation of Large Language Models in Automated Program Repair Benchmarking automated program repair: An extensive study on both real-world and artificial bugs,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.694450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.463552Z digest=sha256:ba2728f00b03675f3f017816c7793586c9675f4c366c567a6c41ff3b617508c3

Observation 3742ddc5-6f61-4290-956f-49029b7ae247 · outbound

This paper cites A large-scale empirical review of patch correctness checking approaches,.

Empirical Evaluation of Large Language Models in Automated Program Repair A large-scale empirical review of patch correctness checking approaches,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.684923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.466363Z digest=sha256:93e4157519da1a869f3da6daa4a0ba17df2291d8d4896890e80f373318989fc0

Observation 22b224c3-c84b-4ba9-be58-302809035acd · outbound

This paper cites Fine-grained and accurate source code differencing,.

Empirical Evaluation of Large Language Models in Automated Program Repair Fine-grained and accurate source code differencing,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.675707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.469686Z digest=sha256:522f63cc91843203d6456f81c86fe7360555c12049cc1d1db165b88cd1b54516

Observation 31906295-cc80-4353-beac-7113e8e9715b · outbound

This paper cites Hyperparameter optimiza- tion for ast differencing,.

Empirical Evaluation of Large Language Models in Automated Program Repair Hyperparameter optimiza- tion for ast differencing,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.665562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.472880Z digest=sha256:a6c9266fe180a7250b5d64de48184198479b4665fe58066cbe45bc2ffcd28291

Observation e5d92750-57d9-4d2c-a8aa-24c3189299a2 · outbound

This paper cites Available: https://proceedings.neurips.cc/paper files/ paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf.

Empirical Evaluation of Large Language Models in Automated Program Repair Available: https://proceedings.neurips.cc/paper files/ paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf

Reference 1901

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:05.454169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:05.454169Z digest=sha256:e2417ff8625f6eef7ad19433514fd25499e84d8964809cb0c30fee527e410715

Observation 59f72b53-4217-48de-9a4c-7f0376aba95d · outbound

This paper cites Available: https://proceedings.neurips.cc/paper/2022/ hash/9d5609613524ecf4f15af0f7b31abca4-Abstract-Conference.html.

Empirical Evaluation of Large Language Models in Automated Program Repair Available: https://proceedings.neurips.cc/paper/2022/ hash/9d5609613524ecf4f15af0f7b31abca4-Abstract-Conference.html

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:42:05.758987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:42:05.438664Z digest=sha256:ca44b62a5d334151702dae6664107b7a461da9e979cd4e5977e0f07397c377a7

Pith citing papers

Observation 6827e5a6-d000-403b-bcf7-ea2837457152 · inbound

Automating Computational Reproducibility in Social Science: Comparing Prompt-Based and Agent-Based Approaches cites this paper.

Automating Computational Reproducibility in Social Science: Comparing Prompt-Based and Agent-Based Approaches Empirical Evaluation of Large Language Models in Automated Program Repair

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-16T05:57:24.435042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T05:55:48.203213Z digest=sha256:013c3a5a957daea510f08563cb036d58e06b21e855650fe61d4f9f10e94d88b7

Observation 431b66bc-afd3-450e-bfd8-2ebc102b0793 · inbound

Semantic Drift in Bug Resolution: How Behavioral Signals Propagate from Reports to Tests and Patches cites this paper.

Semantic Drift in Bug Resolution: How Behavioral Signals Propagate from Reports to Tests and Patches Empirical Evaluation of Large Language Models in Automated Program Repair

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-01T15:06:55.050376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T15:06:55.050376Z digest=sha256:8574b58f1d2e1f2ae7a133805950331be13d608f9ddc3e5f97b11f0b40539ff8