Paper Citation Record · LEDGER

Large Language Models for Code Generation: The Practitioners Perspective

As of 10 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 4 inbound Pith citation observations for arXiv:2501.16998.

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

pith.paper-citation-record.v1
2501.16998 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T05:17:24.424275Z

measured 51 of 51 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T20:35:53.084536Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T22:34:23.789200Z

Reference resolution

47 of 47 outbound references displayed

verified exact0
verified fuzzy17
unresolved30
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cee79229-1711-4863-8ef3-b1da31c92098 · outbound

This paper cites In: Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering.

Large Language Models for Code Generation: The Practitioners Perspective In: Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:25.025758Z

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 b93e93cf-8575-402c-9a0a-da5995221790 · outbound

This paper cites An In-depth Look at Gemini's Language Abilities.

Large Language Models for Code Generation: The Practitioners Perspective An In-depth Look at Gemini's Language Abilities

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.246821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a73a7ec-0ac2-4d8e-ac94-52005999065a · outbound

This paper cites Program Synthesis with Large Language Models.

Large Language Models for Code Generation: The Practitioners Perspective Program Synthesis with Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.251305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d993891-05f6-429e-b9ee-60bc88b3408e · outbound

This paper cites If you use this software, please cite it using these metadata58 (2021).

Large Language Models for Code Generation: The Practitioners Perspective If you use this software, please cite it using these metadata58 (2021)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:25.014953Z

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 dfa075f7-d5e3-44ac-9f40-ad922c609203 · outbound

This paper cites Journal of Methods and Measurement in the Social Sciences6(1), 14–29 (2015).

Large Language Models for Code Generation: The Practitioners Perspective Journal of Methods and Measurement in the Social Sciences6(1), 14–29 (2015)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.259709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0e3d14d-6f50-4092-ad46-d883edf4dd15 · outbound

This paper cites IEEE Transactions on Software Engineering 49(7), 3675–3691 (2023).

Large Language Models for Code Generation: The Practitioners Perspective IEEE Transactions on Software Engineering 49(7), 3675–3691 (2023)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.996564Z

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 dd9abdf9-1e01-4ae6-965e-ee167bc87db8 · outbound

This paper cites In: Proceedings of the 12th ACM/IEEE international symposium on empirical software engineering and mea- surement.

Large Language Models for Code Generation: The Practitioners Perspective In: Proceedings of the 12th ACM/IEEE international symposium on empirical software engineering and mea- surement

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.985991Z

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 0885cdea-2575-4c7d-af7e-7a0cd13f274d · outbound

This paper cites CodeT: Code Generation with Generated Tests.

Large Language Models for Code Generation: The Practitioners Perspective CodeT: Code Generation with Generated Tests

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.272445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a00d97ed-3e0b-4b67-ab91-6e98bc517b4e · outbound

This paper cites A Survey on Evaluating Large Language Models in Code Generation Tasks.

Large Language Models for Code Generation: The Practitioners Perspective A Survey on Evaluating Large Language Models in Code Generation Tasks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.276536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1402e3f9-2eb2-4469-a4a5-d554ea2d1f6f · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Large Language Models for Code Generation: The Practitioners Perspective Evaluating Large Language Models Trained on Code

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.280922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5a4c1b9-9850-4a00-a740-03b510422137 · outbound

This paper cites arXiv preprint arXiv:2407.06153 (2024) Large Language Models for Code Generation: The Practitioners’ Perspective 19.

Large Language Models for Code Generation: The Practitioners Perspective arXiv preprint arXiv:2407.06153 (2024) Large Language Models for Code Generation: The Practitioners’ Perspective 19

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.285096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb0cb359-d9d5-44e8-8959-54c7b7d08051 · outbound

This paper cites ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generation.

Large Language Models for Code Generation: The Practitioners Perspective ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.288734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84c55678-5c5d-4a49-a07a-265bd1e5a761 · outbound

This paper cites arXiv preprint arXiv:2402.00689 (2024).

Large Language Models for Code Generation: The Practitioners Perspective arXiv preprint arXiv:2402.00689 (2024)

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.292574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78f9c4ed-b8a5-47d9-8499-8e1adc383cc6 · outbound

This paper cites In: 2023 IEEE/ACM International Conference on Software Engineering: Future of Software Engineering (ICSE-FoSE).

Large Language Models for Code Generation: The Practitioners Perspective In: 2023 IEEE/ACM International Conference on Software Engineering: Future of Software Engineering (ICSE-FoSE)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.974299Z

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 28eb0d3d-3e5c-4c8a-9d7c-a7880c8cf4b3 · outbound

This paper cites InCoder: A Generative Model for Code Infilling and Synthesis.

Large Language Models for Code Generation: The Practitioners Perspective InCoder: A Generative Model for Code Infilling and Synthesis

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.300010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16cd22ae-d5ad-4be6-80c0-68677ca03906 · outbound

This paper cites arXiv e-prints pp.

Large Language Models for Code Generation: The Practitioners Perspective arXiv e-prints pp

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.962342Z

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 a0242311-5784-4bce-8d13-0dc37239f411 · outbound

This paper cites Field methods18(1), 59–82 (2006).

Large Language Models for Code Generation: The Practitioners Perspective Field methods18(1), 59–82 (2006)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.951434Z

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 a956df3c-1c0c-46ea-95c7-a1f9a24a0259 · outbound

This paper cites Measuring Coding Challenge Competence With APPS.

Large Language Models for Code Generation: The Practitioners Perspective Measuring Coding Challenge Competence With APPS

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.312552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46b7a53c-6a06-45cb-a1dc-6534f77cee0c · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.

Large Language Models for Code Generation: The Practitioners Perspective MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.316434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26ec3d10-340a-485f-a7bd-d7a30311bb53 · outbound

This paper cites In: Guide to advanced empirical software engineering, pp.

Large Language Models for Code Generation: The Practitioners Perspective In: Guide to advanced empirical software engineering, pp

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.940212Z

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 2b21b73f-3070-4d9e-b59e-e137bc553023 · outbound

This paper cites an unresolved cited work.

Large Language Models for Code Generation: The Practitioners Perspective Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-10T05:17:24.929350Z

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 1424952f-b224-4f79-ad50-3701bff1f058 · outbound

This paper cites Knowledge Manage- ment & E-Learning13(4), 408 (2021).

Large Language Models for Code Generation: The Practitioners Perspective Knowledge Manage- ment & E-Learning13(4), 408 (2021)

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.918230Z

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 06a302f3-0664-4d7e-b314-5081b78610e3 · outbound

This paper cites Science378(6624), 1092–1097 (2022).

Large Language Models for Code Generation: The Practitioners Perspective Science378(6624), 1092–1097 (2022)

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.331726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07dc9976-6858-47b7-926f-588091243726 · outbound

This paper cites ACM Transactions on Software Engineering and Methodology (2024).

Large Language Models for Code Generation: The Practitioners Perspective ACM Transactions on Software Engineering and Methodology (2024)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.900255Z

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 cc18877f-ec51-482b-b318-5fe06c4e6acf · outbound

This paper cites Generative Artificial Intelligence for Software Engineering -- A Research Agenda.

Large Language Models for Code Generation: The Practitioners Perspective Generative Artificial Intelligence for Software Engineering -- A Research Agenda

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.339000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41f028a2-1b17-413e-8a38-96032a2f8012 · outbound

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

Large Language Models for Code Generation: The Practitioners Perspective CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.343112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6594ab14-8406-4000-bfa9-d9c5b8778339 · outbound

This paper cites HumanEval-XL: A Multilingual Code Generation Benchmark for Cross-lingual Natural Language Generalization.

Large Language Models for Code Generation: The Practitioners Perspective HumanEval-XL: A Multilingual Code Generation Benchmark for Cross-lingual Natural Language Generalization

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.347029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9704be8e-a1b3-46e0-8640-b35db7eb76fd · outbound

This paper cites CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks.

Large Language Models for Code Generation: The Practitioners Perspective CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.350947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 995a4f70-e11e-4fa7-8120-3fe05ee943f2 · outbound

This paper cites ChatDev: Communicative Agents for Software Development.

Large Language Models for Code Generation: The Practitioners Perspective ChatDev: Communicative Agents for Software Development

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.354569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0b2e4da-e849-47ba-ab83-ada25867022e · outbound

This paper cites TimeLess: A Vision for the Next Generation of Software Development.

Large Language Models for Code Generation: The Practitioners Perspective TimeLess: A Vision for the Next Generation of Software Development

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.359253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4c14c1c-4049-468c-83ca-3db28b37687f · outbound

This paper cites Autonomous Agents in Software Development: A Vision Paper.

Large Language Models for Code Generation: The Practitioners Perspective Autonomous Agents in Software Development: A Vision Paper

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.362847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ddd093b-141c-47af-bcd1-eaa27aba0f76 · outbound

This paper cites CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology.

Large Language Models for Code Generation: The Practitioners Perspective CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.366515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 208d1f50-9185-46ea-b473-d9597982af39 · outbound

This paper cites In: ICLR 2024 Workshop on Large Language Model (LLM) Agents.

Large Language Models for Code Generation: The Practitioners Perspective In: ICLR 2024 Workshop on Large Language Model (LLM) Agents

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.889381Z

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 b33719e0-34ce-46e5-b950-7e1516cc4691 · outbound

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

Large Language Models for Code Generation: The Practitioners Perspective Code Llama: Open Foundation Models for Code

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.375110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc628ed2-c44e-45d0-b0f6-edb216928283 · outbound

This paper cites Empirical software engineering14, 131–164 (2009).

Large Language Models for Code Generation: The Practitioners Perspective Empirical software engineering14, 131–164 (2009)

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.878470Z

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 5b478f3a-a5ee-465f-b490-3b6f6c7bd9c5 · outbound

This paper cites In: International Conference on Product-Focused Software Process Improvement.

Large Language Models for Code Generation: The Practitioners Perspective In: International Conference on Product-Focused Software Process Improvement

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.867172Z

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 fbb9c020-8249-4120-a964-16c9a4fb1020 · outbound

This paper cites ACM Transactions on Design Automation of Electronic Systems29(3), 1–31 (2024).

Large Language Models for Code Generation: The Practitioners Perspective ACM Transactions on Design Automation of Electronic Systems29(3), 1–31 (2024)

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.385945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 398989e1-27ff-4389-a083-345b62a1c678 · outbound

This paper cites O’Reilly Media, Inc.

Large Language Models for Code Generation: The Practitioners Perspective O’Reilly Media, Inc

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.849377Z

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 5973aeea-af97-4309-a6a4-0191ab63ecca · outbound

This paper cites an unresolved cited work.

Large Language Models for Code Generation: The Practitioners Perspective Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-10T05:17:24.838275Z

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 5a7c0e9d-fb69-4d2a-ba5d-afe50fcb9a1b · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Large Language Models for Code Generation: The Practitioners Perspective Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.396302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52210bb1-3c7c-4352-8bbc-e5ae78367276 · outbound

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

Large Language Models for Code Generation: The Practitioners Perspective CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.401154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5041e39-9161-4aa6-83bf-01daf12a628c · outbound

This paper cites Web engineering pp.

Large Language Models for Code Generation: The Practitioners Perspective Web engineering pp

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.827526Z

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 6b201368-da1d-49ed-a82f-a2ed1fc58050 · outbound

This paper cites In: Proceedings of the 6th ACM SIGPLAN International Symposium on Machine Programming.

Large Language Models for Code Generation: The Practitioners Perspective In: Proceedings of the 6th ACM SIGPLAN International Symposium on Machine Programming

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.816560Z

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 a0e2bcc0-6486-47dd-9f7f-a232f7286409 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence (2024).

Large Language Models for Code Generation: The Practitioners Perspective IEEE Transactions on Pattern Analysis and Machine Intelligence (2024)

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:17:24.805449Z

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 c150c301-be29-4fdf-bb22-f09e015fe160 · outbound

This paper cites Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task.

Large Language Models for Code Generation: The Practitioners Perspective Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.416533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5213d168-bbe7-448a-b0dc-7e2d3012a5f3 · outbound

This paper cites CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X.

Large Language Models for Code Generation: The Practitioners Perspective CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.420590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb4c03f4-8390-4465-8ad2-d5a6095bd67d · outbound

This paper cites A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends.

Large Language Models for Code Generation: The Practitioners Perspective A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-10T05:17:24.424275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 6ab19358-bddd-4f91-bef1-963ed71fc0ee · inbound

LLM-Generated Microservice Implementations from RESTful API Definitions cites this paper.

LLM-Generated Microservice Implementations from RESTful API Definitions Large Language Models for Code Generation: The Practitioners Perspective

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T20:35:53.084536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a66cb3ab-2674-4dd3-99ff-43fee1d1bf4f · inbound

Perspective on Utilizing Foundation Models for Laboratory Automation in Materials Research cites this paper.

Perspective on Utilizing Foundation Models for Laboratory Automation in Materials Research Large Language Models for Code Generation: The Practitioners Perspective

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T00:55:16.871200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 765f7a1b-af90-4df8-950d-a93555aa4964 · inbound

A Pilot Study on LLM-Based Agentic Translation from Android to iOS: Pitfalls and Insights cites this paper.

A Pilot Study on LLM-Based Agentic Translation from Android to iOS: Pitfalls and Insights Large Language Models for Code Generation: The Practitioners Perspective

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T15:24:09.726168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4118927-bdd8-4479-8bf5-4373e4ecbd38 · inbound

TusoAI: Agentic Optimization for Scientific Methods cites this paper.

TusoAI: Agentic Optimization for Scientific Methods Large Language Models for Code Generation: The Practitioners Perspective

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:34:23.791229Z

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.