Paper Citation Record · LEDGER

Combining Large Language Models with Static Analyzers for Code Review Generation

As of 10 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 3 inbound Pith citation observations for arXiv:2502.06633.

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

pith.paper-citation-record.v1
2502.06633 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:53:29.007007Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:13:28.983443Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T04:12:02.960470Z

Reference resolution

62 of 62 outbound references displayed

verified exact1
verified fuzzy29
unresolved32
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 83c19557-aa49-44f0-865b-3eee16e3b4b3 · outbound

This paper cites A review of code reviewer recommendation studies: Challenges and future directions,.

Combining Large Language Models with Static Analyzers for Code Review Generation A review of code reviewer recommendation studies: Challenges and future directions,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.962343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 484bf358-850e-46de-b257-5be1169c1190 · outbound

This paper cites A survey on source code review using machine learning,.

Combining Large Language Models with Static Analyzers for Code Review Generation A survey on source code review using machine learning,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.953463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 309a958d-b0cd-4a3d-91b2-05d5cf0d46d2 · outbound

This paper cites Com- mentfinder: a simpler, faster, more accurate code review comments recommendation,.

Combining Large Language Models with Static Analyzers for Code Review Generation Com- mentfinder: a simpler, faster, more accurate code review comments recommendation,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:27.895175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e5bc63f-9066-4fc5-ad49-28ee9d6baee2 · outbound

This paper cites Four eyes are better than two: On the impact of code reviews on software quality,.

Combining Large Language Models with Static Analyzers for Code Review Generation Four eyes are better than two: On the impact of code reviews on software quality,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:27.898595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2130f27-3a47-4919-9e79-048e5681b8c8 · outbound

This paper cites Improving the learning of code review successive tasks with cross-task knowledge distillation,.

Combining Large Language Models with Static Analyzers for Code Review Generation Improving the learning of code review successive tasks with cross-task knowledge distillation,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:27.902364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a493d42b-0bc9-4a28-8fd0-77224b43bc2b · outbound

This paper cites Finding bugs is easy,.

Combining Large Language Models with Static Analyzers for Code Review Generation Finding bugs is easy,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.925436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 121d58a3-e1a8-48ca-b958-7293a49ac63d · outbound

This paper cites Tricorder: Building a program analysis ecosystem,.

Combining Large Language Models with Static Analyzers for Code Review Generation Tricorder: Building a program analysis ecosystem,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.916332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d3312437-0f25-4b2d-afc4-e93f0f4fdbec · outbound

This paper cites Core: Resolving code quality issues using llms,.

Combining Large Language Models with Static Analyzers for Code Review Generation Core: Resolving code quality issues using llms,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.905867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d859a51f-4257-48f3-bbff-cf31b5471d77 · outbound

This paper cites Code review automation: strengths and weaknesses of the state of the art,.

Combining Large Language Models with Static Analyzers for Code Review Generation Code review automation: strengths and weaknesses of the state of the art,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:27.917480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b27b1b15-167c-42e5-83c7-f742dbf91c84 · outbound

This paper cites Towards contextually aware large language models for software requirements engineering: A retrieval augmented generation framework,.

Combining Large Language Models with Static Analyzers for Code Review Generation Towards contextually aware large language models for software requirements engineering: A retrieval augmented generation framework,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.888509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f62df501-85bd-4a56-a6ee-004e8cd73a8e · outbound

This paper cites Core: Automating review recommendation for code changes,.

Combining Large Language Models with Static Analyzers for Code Review Generation Core: Automating review recommendation for code changes,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.802596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51abefd3-d5c6-4b86-aea9-4e55148a674b · outbound

This paper cites Automating code review,.

Combining Large Language Models with Static Analyzers for Code Review Generation Automating code review,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.665430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51194e5b-e0b1-4e78-bd48-8087977d1c4e · outbound

This paper cites A survey on modern code review: Progresses, challenges and opportunities,.

Combining Large Language Models with Static Analyzers for Code Review Generation A survey on modern code review: Progresses, challenges and opportunities,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.059611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 701ee320-dd3f-4d42-9b80-77f3ab6c2509 · outbound

This paper cites Code generation using machine learning: A systematic review,.

Combining Large Language Models with Static Analyzers for Code Review Generation Code generation using machine learning: A systematic review,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.510706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 57c9f736-d276-477e-abcd-cd6de2447932 · outbound

This paper cites Evaluating how static analysis tools can reduce code review effort,.

Combining Large Language Models with Static Analyzers for Code Review Generation Evaluating how static analysis tools can reduce code review effort,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.354722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1edc54cb-e65c-4c52-808f-7b684d27fb91 · outbound

This paper cites Evaluating bug finders– test and measurement of static code analyzers,.

Combining Large Language Models with Static Analyzers for Code Review Generation Evaluating bug finders– test and measurement of static code analyzers,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.196515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e6e777fd-3786-4219-b84d-7738636cb218 · outbound

This paper cites Using static analysis to find bugs,.

Combining Large Language Models with Static Analyzers for Code Review Generation Using static analysis to find bugs,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.153241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7d02667-50e1-487b-8ced-713548a46af8 · outbound

This paper cites On adopting linters to deal with performance concerns in android apps,.

Combining Large Language Models with Static Analyzers for Code Review Generation On adopting linters to deal with performance concerns in android apps,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.179361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d8450cd1-49b8-4133-8328-f4f9b14fc43c · outbound

This paper cites FindBugs,.

Combining Large Language Models with Static Analyzers for Code Review Generation FindBugs,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.168990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 20302845-1347-4981-8e4d-66cd45ecd8c8 · outbound

This paper cites an unresolved cited work.

Combining Large Language Models with Static Analyzers for Code Review Generation Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-08T14:53:30.157652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a4acf75-9da9-4150-bbfc-f9ddcc48f33b · outbound

This paper cites Checkstyle,.

Combining Large Language Models with Static Analyzers for Code Review Generation Checkstyle,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.147656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation abe26048-68d9-41e2-aac3-eb2c78eafc84 · outbound

This paper cites SonarQube,.

Combining Large Language Models with Static Analyzers for Code Review Generation SonarQube,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.138356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d332c3e3-a1f7-42fe-9178-6083088cc70c · outbound

This paper cites Static code analysis tools: A systematic literature review,.

Combining Large Language Models with Static Analyzers for Code Review Generation Static code analysis tools: A systematic literature review,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.128194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 71d10bdf-5c83-4b1d-bdd0-57005e204511 · outbound

This paper cites Analyzing the state of static analysis: A large-scale evaluation in open source software,.

Combining Large Language Models with Static Analyzers for Code Review Generation Analyzing the state of static analysis: A large-scale evaluation in open source software,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:30.027905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation eba54aaf-64a4-4ad7-af34-a5173f0873f4 · outbound

This paper cites Automating code review activities by large-scale pre-training,.

Combining Large Language Models with Static Analyzers for Code Review Generation Automating code review activities by large-scale pre-training,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.182021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e384db6c-0d7a-4cc7-b342-3c2b8e8a1e6b · outbound

This paper cites Using pre-trained models to boost code review automa- tion,.

Combining Large Language Models with Static Analyzers for Code Review Generation Using pre-trained models to boost code review automa- tion,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.187479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation deb7f4d0-3bb2-41b3-9bbf-1aa9c8daf620 · outbound

This paper cites Reducing human effort and improving quality in peer code reviews using automatic static analysis and reviewer recommenda- tion,.

Combining Large Language Models with Static Analyzers for Code Review Generation Reducing human effort and improving quality in peer code reviews using automatic static analysis and reviewer recommenda- tion,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.858354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ae2759db-28d0-4277-952b-0223e0986faf · outbound

This paper cites Auger: automatically generating review comments with pre-training models,.

Combining Large Language Models with Static Analyzers for Code Review Generation Auger: automatically generating review comments with pre-training models,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.195211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a667ca53-4a09-4533-ad72-88f9a4a20093 · outbound

This paper cites Llama-reviewer: Advancing code review automation with large language models through parameter- efficient fine-tuning,.

Combining Large Language Models with Static Analyzers for Code Review Generation Llama-reviewer: Advancing code review automation with large language models through parameter- efficient fine-tuning,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.198229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b5deb44-b686-4a34-9c61-a80477ff4e54 · outbound

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

Combining Large Language Models with Static Analyzers for Code Review Generation CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.201141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc121efc-b409-4764-8229-63bd41fe4eb8 · outbound

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

Combining Large Language Models with Static Analyzers for Code Review Generation StarCoder: may the source be with you!

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.204402Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98ff8667-1283-4d1a-a0d1-07c62a577cec · outbound

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

Combining Large Language Models with Static Analyzers for Code Review Generation Code Llama: Open Foundation Models for Code

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.207390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b264a84-2a95-412d-8446-2f6b2de305d6 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Combining Large Language Models with Static Analyzers for Code Review Generation Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.211037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a068d9fd-5fdd-4cab-bd1b-171a84d7fcf8 · outbound

This paper cites Business insights using rag–llms: a review and case study,.

Combining Large Language Models with Static Analyzers for Code Review Generation Business insights using rag–llms: a review and case study,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.768328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 41ba364e-012f-4f11-b129-c16901d71963 · outbound

This paper cites JudgeLM: Fine-tuned Large Language Models are Scalable Judges.

Combining Large Language Models with Static Analyzers for Code Review Generation JudgeLM: Fine-tuned Large Language Models are Scalable Judges

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.217178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f481dd0-e21a-42e4-94e0-57c9bc5d026f · outbound

This paper cites Judging the judges: A systematic investigation of position bias in pairwise comparative assessments by llms,.

Combining Large Language Models with Static Analyzers for Code Review Generation Judging the judges: A systematic investigation of position bias in pairwise comparative assessments by llms,

Reference 36

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Source-reported events for the cited work

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Observation 574feeb1-6552-48a2-b94f-952ed453f52c · outbound

This paper cites Judging the Judges: Evaluating Alignment and Vulnerabilities in LLMs-as-Judges.

Combining Large Language Models with Static Analyzers for Code Review Generation Judging the Judges: Evaluating Alignment and Vulnerabilities in LLMs-as-Judges

Reference 37

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Observation 7a440774-f6d6-4ac8-a00b-3af8c9dfb55f · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena,.

Combining Large Language Models with Static Analyzers for Code Review Generation Judging llm-as-a-judge with mt-bench and chatbot arena,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.399912Z

Source-reported events for the cited work

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Observation 0ef31e88-6e83-4422-961c-ee72df011cbb · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Combining Large Language Models with Static Analyzers for Code Review Generation LoRA: Low-Rank Adaptation of Large Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.465043Z

Source-reported events for the cited work

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Observation b5448c10-b63e-4e57-9f66-207f4489a2e0 · outbound

This paper cites A critical comparison on six static analysis tools: Detection, agreement, and precision,.

Combining Large Language Models with Static Analyzers for Code Review Generation A critical comparison on six static analysis tools: Detection, agreement, and precision,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.695082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cc284a4e-a2ca-4295-98c6-f04fe33fc4f5 · outbound

This paper cites Comparing bug finding tools for java open source software,.

Combining Large Language Models with Static Analyzers for Code Review Generation Comparing bug finding tools for java open source software,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.684511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7fc557cd-8a12-43d4-b5b1-0abe6409fa52 · outbound

This paper cites Why don’t software developers use static analysis tools to find bugs?.

Combining Large Language Models with Static Analyzers for Code Review Generation Why don’t software developers use static analysis tools to find bugs?

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.631767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d69c5218-1fd9-4396-81b1-04941acb1e07 · outbound

This paper cites The effectiveness of supervised machine learning algorithms in predicting software refac- toring,.

Combining Large Language Models with Static Analyzers for Code Review Generation The effectiveness of supervised machine learning algorithms in predicting software refac- toring,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.667465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 528a6519-123d-4419-8d44-748382b5dbf5 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena,.

Combining Large Language Models with Static Analyzers for Code Review Generation Judging llm-as-a-judge with mt-bench and chatbot arena,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.640064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b67cbc0-95b8-43ef-86fd-5d34564de8ec · outbound

This paper cites An Empirical Study of LLM-as-a-Judge for LLM Evaluation: Fine-tuned Judge Model is not a General Substitute for GPT-4.

Combining Large Language Models with Static Analyzers for Code Review Generation An Empirical Study of LLM-as-a-Judge for LLM Evaluation: Fine-tuned Judge Model is not a General Substitute for GPT-4

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.643250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ff770ba-08cd-47ca-a682-7d1d4e8a8588 · outbound

This paper cites CodeUltraFeedback: An LLM-as-a-Judge Dataset for Aligning Large Language Models to Coding Preferences.

Combining Large Language Models with Static Analyzers for Code Review Generation CodeUltraFeedback: An LLM-as-a-Judge Dataset for Aligning Large Language Models to Coding Preferences

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.646885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 683141a4-8069-4a43-b52a-e187aa625541 · outbound

This paper cites Active Retrieval Augmented Generation.

Combining Large Language Models with Static Analyzers for Code Review Generation Active Retrieval Augmented Generation

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.650661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df6f92df-3623-41c0-8aea-fa9ea5cd769d · outbound

This paper cites Replication package,.

Combining Large Language Models with Static Analyzers for Code Review Generation Replication package,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.649002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 129583c9-3b4d-4c5c-835e-bd965a9d6409 · outbound

This paper cites Datasets and results,.

Combining Large Language Models with Static Analyzers for Code Review Generation Datasets and results,

Reference 49

Resolution: verified exact; raw_fallback, observed 2026-08-08T14:53:29.261940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3123a59b-2aee-49fe-96a3-b9cefe439504 · outbound

This paper cites Interrater reliability: the kappa statistic,.

Combining Large Language Models with Static Analyzers for Code Review Generation Interrater reliability: the kappa statistic,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.661040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92563325-43a9-4e9a-8820-ff2a21b14546 · outbound

This paper cites Intelligent code reviews using deep learning,.

Combining Large Language Models with Static Analyzers for Code Review Generation Intelligent code reviews using deep learning,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.631915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51549220-8e37-44f3-852b-1d2421138151 · outbound

This paper cites Towards automating code review activities,.

Combining Large Language Models with Static Analyzers for Code Review Generation Towards automating code review activities,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.613238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 970ed84c-aad0-4414-a5a8-c7704ad8e0e1 · outbound

This paper cites RepairAgent: An Autonomous, LLM-Based Agent for Program Repair.

Combining Large Language Models with Static Analyzers for Code Review Generation RepairAgent: An Autonomous, LLM-Based Agent for Program Repair

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.672199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64fb9820-be78-4bc3-9906-1ec28cde96a6 · outbound

This paper cites Pyty: Repairing static type errors in python,.

Combining Large Language Models with Static Analyzers for Code Review Generation Pyty: Repairing static type errors in python,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.590135Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 66527361-54d7-4a08-b06e-46d691047b80 · outbound

This paper cites Learning deep semantics for test completion,.

Combining Large Language Models with Static Analyzers for Code Review Generation Learning deep semantics for test completion,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.577223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ab523caa-3739-440d-818e-3dbd493246b1 · outbound

This paper cites No More Manual Tests? Evaluating and Improving ChatGPT for Unit Test Generation.

Combining Large Language Models with Static Analyzers for Code Review Generation No More Manual Tests? Evaluating and Improving ChatGPT for Unit Test Generation

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.778951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4179e8f-18d2-47f5-be85-e0fc286e9fc8 · outbound

This paper cites An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation.

Combining Large Language Models with Static Analyzers for Code Review Generation An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.940188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 799bc5e6-cfc6-48e2-ab25-c37fbe09b21b · outbound

This paper cites SkipAnalyzer: A Tool for Static Code Analysis with Large Language Models.

Combining Large Language Models with Static Analyzers for Code Review Generation SkipAnalyzer: A Tool for Static Code Analysis with Large Language Models

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.964808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ed94ee0-1c73-466d-aa02-93fbbe63aa7e · outbound

This paper cites Gptscan: Detecting logic vulnerabilities in smart contracts by combining gpt with program analysis,.

Combining Large Language Models with Static Analyzers for Code Review Generation Gptscan: Detecting logic vulnerabilities in smart contracts by combining gpt with program analysis,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:28.996126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5306d91-b898-4e44-a03c-3664e696bbb2 · outbound

This paper cites D2a: A dataset built for ai-based vulnerability detection methods using differential analysis,.

Combining Large Language Models with Static Analyzers for Code Review Generation D2a: A dataset built for ai-based vulnerability detection methods using differential analysis,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.560283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e80e0810-cbba-4a09-a154-4f2c5b2bdd37 · outbound

This paper cites Reposvul: A repository-level high-quality vulnerability dataset,.

Combining Large Language Models with Static Analyzers for Code Review Generation Reposvul: A repository-level high-quality vulnerability dataset,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:53:29.549684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e0fd9c19-07fb-4036-a591-a78b6d9c9738 · outbound

This paper cites STALL+: Boosting LLM-based Repository-level Code Completion with Static Analysis.

Combining Large Language Models with Static Analyzers for Code Review Generation STALL+: Boosting LLM-based Repository-level Code Completion with Static Analysis

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-08T14:53:29.007007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 0891ab40-109b-405c-8711-a0ca8d557998 · inbound

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review cites this paper.

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review Combining Large Language Models with Static Analyzers for Code Review Generation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T12:13:28.983443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67e05e48-4a7d-4fa1-a577-cb5794e98a98 · inbound

MetaLint: Easy-to-Hard Generalization for Code Linting cites this paper.

MetaLint: Easy-to-Hard Generalization for Code Linting Combining Large Language Models with Static Analyzers for Code Review Generation

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-19T04:12:02.962212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b6efdf94-a470-4cf3-9087-146935cf5588 · inbound

SWR-Bench: Assessing LLM Performance in Real-World Code Review Comment Generation cites this paper.

SWR-Bench: Assessing LLM Performance in Real-World Code Review Comment Generation Combining Large Language Models with Static Analyzers for Code Review Generation

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-05T12:32:26.104645Z

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Unavailable: canonical work link unavailable.