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Paper Citation Record · LEDGER

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality

As of 8 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 4 inbound Pith citation observations for arXiv:2509.10402.

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

pith.paper-citation-record.v1
2509.10402 v1

Coverage vector

measured 83 of 83 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:57:07.661469Z

measured 87 of 87 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:51:02.423350Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:20:06.998087Z

Reference resolution

83 of 83 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved83
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8b1c8119-79b2-4fb9-857f-41701b16460f · outbound

This paper cites Analysis of ChatGPT-Generated Codes Across Multiple Programming Languages,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Analysis of ChatGPT-Generated Codes Across Multiple Programming Languages,

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:04.770188Z digest=sha256:8730f4fec2bfb223b66a159c5bbe59d89733b4dd5a8262947f8fa54562846e05

Observation 489381b5-1785-4e2a-964a-994410ffd9bd · outbound

This paper cites Anthropic economic index: Ai’s impact on software development,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Anthropic economic index: Ai’s impact on software development,

Reference 2

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source=pdf_text observed=2026-08-04T17:57:04.807594Z digest=sha256:8727c5638a7ee9fed66430572d94f72e47f5519103db78817afd5ba0e018e748

Observation 9accfd1d-92a6-48db-b489-7e5fce2679c6 · outbound

This paper cites Artifacts are now generally available,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Artifacts are now generally available,

Reference 3

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source=pdf_text observed=2026-08-04T17:57:04.842492Z digest=sha256:e9894c5631c76a6cfb1dca14156467cad4994824d88759638f614067f559d9ea

Observation 44ea2a3d-9f87-4741-b74d-b368773302c9 · outbound

This paper cites Claude ai: Next-generation ai assistant,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Claude ai: Next-generation ai assistant,

Reference 4

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source=pdf_text observed=2026-08-04T17:57:04.872797Z digest=sha256:e300a3fd70020541d52f503dc3eb8be1d88c2a029523b3149e4d075d9a86d2a9

Observation faf5a67c-3ffb-49f2-8a7c-9d1a73b6f05c · outbound

This paper cites Privacy policy,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Privacy policy,

Reference 5

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source=pdf_text observed=2026-08-04T17:57:04.928462Z digest=sha256:b8c17a1516107178abf8c526797da074266b8d0766feaf73a0488d7e5bf87c2e

Observation 3d3bd517-9fc4-4b4b-95a8-158085ed9b33 · outbound

This paper cites Cursor: The ai code editor,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Cursor: The ai code editor,

Reference 6

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source=pdf_text observed=2026-08-04T17:57:04.965924Z digest=sha256:92ac45a277a27959bc31411780e90615d83ae132fdda31a609cbdac0939c24bb

Observation 6660be13-29d8-4862-9464-a19e9857c8f4 · outbound

This paper cites Evaluation of rust code verbosity, understandability and complexity,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Evaluation of rust code verbosity, understandability and complexity,

Reference 7

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source=pdf_text observed=2026-08-04T17:57:05.031795Z digest=sha256:a53c23b8dc2adf35c8f2309a4c808d9c3bffdee0a98876dee39e1bb356bf997c

Observation 063e1ce5-52cb-4fdd-ab4d-8e4e26a309a8 · outbound

This paper cites Title or description of the website,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Title or description of the website,

Reference 8

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source=pdf_text observed=2026-08-04T17:57:05.081412Z digest=sha256:e8dcf7e83cc956215f7d135443a06b2bc6e15c837f5d0fcc3f23cce2823376d4

Observation 6305e748-b880-4d77-b526-41eeaab19b01 · outbound

This paper cites Density-Based Clustering Based on Hierarchical Density Estimates,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Density-Based Clustering Based on Hierarchical Density Estimates,

Reference 9

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source=pdf_text observed=2026-08-04T17:57:05.127182Z digest=sha256:eda6ce560454e6a030993f386882994e7b7cbd6e8a005059ef5868da758e88c0

Observation 75ec201c-6353-47bb-b6f8-e65a59f98d82 · outbound

This paper cites Vi- cuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Vi- cuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality,

Reference 10

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source=pdf_text observed=2026-08-04T17:57:05.179926Z digest=sha256:3aa6b6ced4eb6f5b84b5f76310620307d51ccb35f31a033063721799b7dec32e

Observation ae5d26c3-1fcd-4c9b-aa1c-1379f1a721fd · outbound

This paper cites CodePrompt: Task-Agnostic Prefix Tuning for Program and Language Generation,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality CodePrompt: Task-Agnostic Prefix Tuning for Program and Language Generation,

Reference 11

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source=pdf_text observed=2026-08-04T17:57:05.270073Z digest=sha256:fd9cd674e0a68beb9d2d709c8f390ac815757219a9d0a05311ac56a65bb55069

Observation a44d9a3a-dfba-4335-a276-87e1111a9a9b · outbound

This paper cites Chollet, “Keras,” https://github.com/keras-team/keras, 2015, accessed: 2025-09-01.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Chollet, “Keras,” https://github.com/keras-team/keras, 2015, accessed: 2025-09-01

Reference 12

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source=pdf_text observed=2026-08-04T17:57:05.326673Z digest=sha256:c08e9db80513b51c0b4a51e73c9fda51b782ebebbc92162ae4191548fc5ab18e

Observation 6579732a-a35e-4a15-8c69-bf925971ff12 · outbound

This paper cites Cline: Ai coding, open source and uncompromised,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Cline: Ai coding, open source and uncompromised,

Reference 13

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source=pdf_text observed=2026-08-04T17:57:05.400329Z digest=sha256:9180912c562559b9c575c6ff2cee933bc2690be0c87e59e3f2f24df8c4e91aff

Observation 12cf916f-7510-4b81-820c-dd566fac787c · outbound

This paper cites A Performance Study of LLM-Generated Code on Leetcode,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality A Performance Study of LLM-Generated Code on Leetcode,

Reference 14

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source=pdf_text observed=2026-08-04T17:57:05.478491Z digest=sha256:2b9c1d285fa786886b9d8085906d2416648545af8145c6302d55a0b5a5860bff

Observation 10707464-6e26-46a7-8a5e-44e49edfff14 · outbound

This paper cites Cppcheck: A static analyzer for c/c++ code,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Cppcheck: A static analyzer for c/c++ code,

Reference 15

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source=pdf_text observed=2026-08-04T17:57:05.515424Z digest=sha256:73f6d1894a7e5783c132a3a9f575e018a8898bc5732b383dfaaf9919e1939a1b

Observation 67aa653d-7c9b-4196-a02f-731d15f9b442 · outbound

This paper cites Multi-Task Learning with Deep Neural Networks: A Survey.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Multi-Task Learning with Deep Neural Networks: A Survey

Reference 16

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source=pdf_text observed=2026-08-04T17:57:05.548979Z digest=sha256:f6657dc119149560f7d37c4e0b1b616ba839e6e3539e83feea30bb2453645e0b

Observation 3d6d2415-537c-4dfb-91a3-df440aaf1c4b · outbound

This paper cites Why Do Developers Engage with ChatGPT in Issue-Tracker? Investigating Usage and Reliance on ChatGPT-Generated Code.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Why Do Developers Engage with ChatGPT in Issue-Tracker? Investigating Usage and Reliance on ChatGPT-Generated Code

Reference 17

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source=pdf_text observed=2026-08-04T17:57:05.579860Z digest=sha256:2d3a1f9b0c79ab59c8e9b45c360d30b6c17bbac941f8f77b2421214d2e138fb6

Observation 960bada6-909e-48ac-acf4-bdd07168dbc1 · outbound

This paper cites Evaluating Privacy Questions from Stack Overflow: Can ChatGPT Compete?.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Evaluating Privacy Questions from Stack Overflow: Can ChatGPT Compete?

Reference 18

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source=pdf_text observed=2026-08-04T17:57:05.610417Z digest=sha256:5f3c440fae60c24f3859c040d619462e635aeae0011121ee0f10b83881572e24

Observation 5da3e3f4-5008-4b10-ada1-aed96eb84286 · outbound

This paper cites Nonparametric pairwise multiple comparisons in indepen- dent groups using dunn’s test,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Nonparametric pairwise multiple comparisons in indepen- dent groups using dunn’s test,

Reference 19

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source=pdf_text observed=2026-08-04T17:57:05.722612Z digest=sha256:a8985d7d8ffe81f0fa57d408cfc2819a800da7658100cf0012de34c66e299184

Observation 81e115a8-44ea-423e-9eff-e5a38b40c371 · outbound

This paper cites Getting started with eslint - pluggable javascript linter,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Getting started with eslint - pluggable javascript linter,

Reference 20

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source=pdf_text observed=2026-08-04T17:57:05.747252Z digest=sha256:bd001912b38ef6b6b136a040a2ce7516cafda6d6191c52c58324b8fee85b4747

Observation 81296a16-7e91-41a1-9d99-2ff7798ebb3a · outbound

This paper cites Investigating Code Generation Performance of ChatGPT with Crowd- sourcing Social Data,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Investigating Code Generation Performance of ChatGPT with Crowd- sourcing Social Data,

Reference 21

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source=pdf_text observed=2026-08-04T17:57:05.758585Z digest=sha256:81b6c4f0ce49efd1d36dff2a29b2ebc45e0f9dcac32dac75dfdeadee9c7d0a4e

Observation af6a11fc-fcc3-4707-a38f-a44c8ff07420 · outbound

This paper cites Mining rule violations in javascript code snippets,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Mining rule violations in javascript code snippets,

Reference 22

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source=pdf_text observed=2026-08-04T17:57:05.795437Z digest=sha256:9a4dcd02b1cffdb87513720a1d0f8831756e0963d5cbdc7441579259155a7be1

Observation ef104fea-074d-4192-8798-b98a581cdcec · outbound

This paper cites Github: Build and ship software on a single, collaborative platform,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Github: Build and ship software on a single, collaborative platform,

Reference 23

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source=pdf_text observed=2026-08-04T17:57:05.845024Z digest=sha256:9a590d09cd58e0da1c041535129080413e843f83ab6f54762870069c70e35cb5

Observation 0f10e34d-8742-441a-a8a9-017cb0595dd2 · outbound

This paper cites BERTopic: Neural topic modeling with a class-based TF-IDF procedure.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality BERTopic: Neural topic modeling with a class-based TF-IDF procedure

Reference 24

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source=pdf_text observed=2026-08-04T17:57:05.877751Z digest=sha256:fcc87898c486de0706d1a9d76f8314b1d4f681b76e8cad2648cfe3465e6ae32c

Observation af23b3f2-1674-4713-a3b9-9ca00dfc1c4c · outbound

This paper cites Bertopic frequently asked questions,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Bertopic frequently asked questions,

Reference 25

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source=pdf_text observed=2026-08-04T17:57:05.922731Z digest=sha256:2644418bec81dbd81c2cb3c83f927defdacfd67c8cd3094c4293b7db0b14c4e3

Observation a3be5d6d-d60e-49b9-a481-86a031878f0e · outbound

This paper cites Bertopic parameter tuning guide,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Bertopic parameter tuning guide,

Reference 26

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source=pdf_text observed=2026-08-04T17:57:05.981510Z digest=sha256:c51ab2a43a46b2fa4e0396a5e75ce8daaf8f8366c67c6efd465c6a17caf19a60

Observation 53f0fd1b-146f-403a-8b71-5afa9c5592f1 · outbound

This paper cites On the Effectiveness of Large Language Models in Domain- Specific Code Generation,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality On the Effectiveness of Large Language Models in Domain- Specific Code Generation,

Reference 27

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source=pdf_text observed=2026-08-04T17:57:06.019342Z digest=sha256:00ed8b34891286a0653e7251dbed47c9e99885571c9a6864ccbce84db48bfe1e

Observation f223ac49-eb59-483f-a659-a48866d021e4 · outbound

This paper cites Prompting and Fine-tuning Large Language Models for Automated Code Review Comment Generation.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Prompting and Fine-tuning Large Language Models for Automated Code Review Comment Generation

Reference 28

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source=pdf_text observed=2026-08-04T17:57:06.023310Z digest=sha256:616e5dc0541824e31a2379ee533b015dc827b384d307d7be5ca59e4f68ea6b03

Observation 5fb9d009-3fa5-4db9-8ed0-6b3f33dad4ec · outbound

This paper cites A modified mann-kendall trend test for autocorrelated data,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality A modified mann-kendall trend test for autocorrelated data,

Reference 29

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source=pdf_text observed=2026-08-04T17:57:06.041557Z digest=sha256:fa9d1e79023618b7dd6237b7d0227c0107e7e4c3a430d7a64544dcd43ef35d48

Observation 38fbd3d7-f07e-476e-9c29-685971d2c45c · outbound

This paper cites An empirical study on developers’ shared conversations with ChatGPT in GitHub pull requests and issues,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality An empirical study on developers’ shared conversations with ChatGPT in GitHub pull requests and issues,

Reference 30

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source=pdf_text observed=2026-08-04T17:57:06.060022Z digest=sha256:ceb2a249207c9836d545f254f24cc064e964fd7c66fb4401f0b00ad41ac57485

Observation 3b1719e7-021d-44fa-b091-16827bdf0f15 · outbound

This paper cites Model context protocol (mcp) at first glance: Studying the security and maintainability of mcp servers,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Model context protocol (mcp) at first glance: Studying the security and maintainability of mcp servers,

Reference 31

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source=pdf_text observed=2026-08-04T17:57:06.109108Z digest=sha256:c9daf04fc54c287e8183e0097d68ee47ca36445709c09f19c1b3b7d2a9de64d4

Observation 95e3feee-b1a6-441d-9104-29e7eb723e0c · outbound

This paper cites CodeCoT: Tackling Code Syntax Errors in CoT Reasoning for Code Generation.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality CodeCoT: Tackling Code Syntax Errors in CoT Reasoning for Code Generation

Reference 32

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source=pdf_text observed=2026-08-04T17:57:06.162203Z digest=sha256:672836b05131749f482bb06efbf1ab1f8cac61b834d4c5aaf502bd66981dee8e

Observation 4e3c78d3-609c-42e6-ad59-d2d0f1361bd8 · outbound

This paper cites A Survey on Large Language Models for Code Generation.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality A Survey on Large Language Models for Code Generation

Reference 33

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source=pdf_text observed=2026-08-04T17:57:06.274165Z digest=sha256:045cbfc02d3012e85140f125c7dd8a080e45e44dac2cbacf7fc8008ac9d1a7b7

Observation 79c1c88f-0458-4f64-a0c2-0e03a92cbe85 · outbound

This paper cites Is Stack Overflow Obsolete? An Empirical Study of the Characteristics of ChatGPT Answers to Stack Overflow Questions.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Is Stack Overflow Obsolete? An Empirical Study of the Characteristics of ChatGPT Answers to Stack Overflow Questions

Reference 34

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source=pdf_text observed=2026-08-04T17:57:06.336023Z digest=sha256:d92ba725087d2178b52865c0f216a2c5f5bad6bfe11febd66a97b9a9ec7e29aa

Observation 14af4d1d-8376-47a2-8039-2b474f2913d4 · outbound

This paper cites Openassistant conversations-democratizing large language model align- ment,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Openassistant conversations-democratizing large language model align- ment,

Reference 35

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source=pdf_text observed=2026-08-04T17:57:06.398263Z digest=sha256:efdd1c823aebfe27d0f61e68b48dd40075de145d3835ec9af4830593ac7fd08a

Observation 6c8588d2-3e21-4fb9-8dd8-79694edcb8c4 · outbound

This paper cites Does code quality affect pull request acceptance? an empirical study,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Does code quality affect pull request acceptance? an empirical study,

Reference 36

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:06.438128Z digest=sha256:461df4de500372f71b0c64aab7fab2cc2a6bb20c646521b911cda4abb48825c4

Observation 99accdda-d1a9-4112-916a-ec03259ac75e · outbound

This paper cites Refining chatgpt-generated code: Characterizing and mitigating code quality issues,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Refining chatgpt-generated code: Characterizing and mitigating code quality issues,

Reference 37

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source=pdf_text observed=2026-08-04T17:57:06.496275Z digest=sha256:4e4f11583cd5a3f79c6eab55881e9c867d7a3263de891ca1c89fd51e4ca74167

Observation 8b95c512-ead7-4356-9bf0-ccffea23e923 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 38

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source=pdf_text observed=2026-08-04T17:57:06.541066Z digest=sha256:d95020f2f39c3dbcf52de0f7393d1e23dd665acad2130e3a054c068676c3bfca

Observation 032e78cb-b712-4927-b2ca-2ea632bec6b5 · outbound

This paper cites Roslyn analyzers github repository,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Roslyn analyzers github repository,

Reference 39

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source=pdf_text observed=2026-08-04T17:57:06.587431Z digest=sha256:309456340a3fffb322e3c1a8cd87f7c06ae9c8328d0fdbcd12606f9c4304d65a

Observation fa85011d-1ff8-454f-ab5c-1ce58f638ed0 · outbound

This paper cites Enhancing user interaction in chatgpt: Characterizing and consolidating multiple prompts for issue resolution,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Enhancing user interaction in chatgpt: Characterizing and consolidating multiple prompts for issue resolution,

Reference 40

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source=pdf_text observed=2026-08-04T17:57:06.633767Z digest=sha256:7834c702546ea644e2c66864b6fe9a1525623cae909078b414c17d30e9fb8423

Observation 5ef97257-2cc8-46e6-a661-2aac772e242a · outbound

This paper cites an unresolved cited work.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Unresolved cited work

Reference 41

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source=pdf_text observed=2026-08-04T17:57:06.732769Z digest=sha256:e1e875f657160087f8987296d94b40de91f3807c3b2ca2317e8a67fd595bed2f

Observation b54ae69b-cfb4-4ace-b6dd-bdb8a0480101 · outbound

This paper cites The content division element,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality The content division element,

Reference 42

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source=pdf_text observed=2026-08-04T17:57:06.880993Z digest=sha256:23f9aa5b8cfb2e73e11644215db07f0e70120a5b8901690ddbe9a9850ac48b1c

Observation 89bd8bfd-d8bd-4d82-8a32-92d18670340e · outbound

This paper cites Image-based communication on social coding platforms,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Image-based communication on social coding platforms,

Reference 43

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source=pdf_text observed=2026-08-04T17:57:06.915483Z digest=sha256:7bd2b6de31261f41f255ee74366a34f2ad79bf79c09349957f306321b44045cb

Observation be51a313-4661-4acd-ad12-19295af0b68b · outbound

This paper cites A Comparison of the Effectiveness of ChatGPT and Co-Pilot for Generating Quality Python Code Solutions,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality A Comparison of the Effectiveness of ChatGPT and Co-Pilot for Generating Quality Python Code Solutions,

Reference 44

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source=pdf_text observed=2026-08-04T17:57:07.007419Z digest=sha256:da3fd3ae0fb402d7c53c8e99073bb793cafd3cbcea2bfd247b875baf4a7f5718

Observation d5750281-a157-4511-9133-5f45c90044e5 · outbound

This paper cites Static analysis warnings and automatic fixing: A replication for C# projects,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Static analysis warnings and automatic fixing: A replication for C# projects,

Reference 45

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source=pdf_text observed=2026-08-04T17:57:07.101742Z digest=sha256:f698e239ae578a4dd69661e713ac0b054555c393008beb07b1b389cbdf3c201c

Observation 9eb18a7c-7e9b-4d3c-ada5-b6a0ae72572e · outbound

This paper cites Chatgpt,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Chatgpt,

Reference 46

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source=pdf_text observed=2026-08-04T17:57:07.156579Z digest=sha256:579c94a710c1e451de9a4ef3ac7b346657545cc427c7171bb1360b3c3ed5d8e2

Observation 6a47d34e-9921-48c6-85b7-caa6634e3289 · outbound

This paper cites Hello gpt-4o,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Hello gpt-4o,

Reference 47

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source=pdf_text observed=2026-08-04T17:57:07.266269Z digest=sha256:c7765eba90df9fc2be777b01f5c5a44864ca94d807f5439cfd2a9f6db99be2e5

Observation 828d99cf-9946-48b1-af6a-596253dcc4e7 · outbound

This paper cites Privacy policy,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Privacy policy,

Reference 48

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source=pdf_text observed=2026-08-04T17:57:07.324503Z digest=sha256:703271f3682944440054c6a9eb83f4115fb24142fe11c2ad5289dbe218b6ac39

Observation 6791e562-f968-41df-886b-2395597f1e41 · outbound

This paper cites tiktoken: A fast bpe tokeniser for use with openai’s models,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality tiktoken: A fast bpe tokeniser for use with openai’s models,

Reference 49

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source=pdf_text observed=2026-08-04T17:57:07.488606Z digest=sha256:6c7ee9d8506a011805c652475870eb271a21a03a15bcf7f73bc07665575f2bd1

Observation 22aa5568-bda8-4e52-a052-56927515cacb · outbound

This paper cites Pytorch: An imperative style, high- performance deep learning library,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Pytorch: An imperative style, high- performance deep learning library,

Reference 50

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source=pdf_text observed=2026-08-04T17:57:07.572722Z digest=sha256:d4c7588b87c28cc0110547bcace5d7ae972740166e988d5eeba802fb77404801

Observation 15314f4b-18b3-4db7-bf0f-bc5ef8200f43 · outbound

This paper cites Pmd - source code analyzer documentation,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Pmd - source code analyzer documentation,

Reference 51

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source=pdf_text observed=2026-08-04T17:57:07.575720Z digest=sha256:234a2dfeb8f943fd68e629a5d45ae396483e4b059fcb1d2d776abaa44c05c09f

Observation 2f4e8a0d-c45f-4830-a3ae-b7e4b60e56b3 · outbound

This paper cites Pylint tutorial and documentation,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Pylint tutorial and documentation,

Reference 52

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source=pdf_text observed=2026-08-04T17:57:07.578604Z digest=sha256:1a1ba7fa71b3f9aad57b2e3e8aec5ebfe9802787cd6eab69dea9f1ac42041164

Observation 33e30072-584d-475b-9c11-efbae158a83c · outbound

This paper cites Black: The uncompromising python code formatter,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Black: The uncompromising python code formatter,

Reference 53

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source=pdf_text observed=2026-08-04T17:57:07.581420Z digest=sha256:d6e5eef7547c0d11a830fb32d44fa01d0b711196247caafaf58dad7036dd18a7

Observation 8ebce97f-5b8a-48fd-a46f-e6d275cabb57 · outbound

This paper cites Dynamic Scoring Code Token Tree: A Novel Decoding Strategy for Generating High-Performance Code,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Dynamic Scoring Code Token Tree: A Novel Decoding Strategy for Generating High-Performance Code,

Reference 54

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source=pdf_text observed=2026-08-04T17:57:07.584161Z digest=sha256:35e1bfccec65aea6d9726ae59be9b759e1e89877724df3a9e61afe4a619257f2

Observation 0800e92a-350a-4297-9d75-6ec8f399b347 · outbound

This paper cites React - the library for web and native user interfaces,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality React - the library for web and native user interfaces,

Reference 55

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source=pdf_text observed=2026-08-04T17:57:07.586839Z digest=sha256:b57786b6a7d6c91b55f05c829ea96951e30ca0fe7971fe2576ffd83a31fff054

Observation b6530847-ec6f-4f62-9395-9352666dc383 · outbound

This paper cites an unresolved cited work.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Unresolved cited work

Reference 56

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source=pdf_text observed=2026-08-04T17:57:07.589430Z digest=sha256:d02af528ae345b9fc889d76da4b3a82fc667267c5d9f02928077ee1cc214a8c9

Observation 66d71783-f9e2-4eb2-932c-a63a36b3d407 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks,

Reference 57

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source=pdf_text observed=2026-08-04T17:57:07.592087Z digest=sha256:27cde9bf5c5dd73216e8098000b7e838e7634d0ac01019b408cba829bad7832f

Observation d7c30d1f-cdd6-4872-b324-9d314606a84e · outbound

This paper cites Exploring the Space of Topic Coherence Measures,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Exploring the Space of Topic Coherence Measures,

Reference 58

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source=pdf_text observed=2026-08-04T17:57:07.594863Z digest=sha256:d27b26dd1afb75dc3e7bab3c7dcd7ef473a47e86cc4133b2560a02f246876edc

Observation 26838de5-ecba-4d19-a979-f6870be7b0ee · outbound

This paper cites The wilcoxon signed rank test for paired comparisons of clustered data,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality The wilcoxon signed rank test for paired comparisons of clustered data,

Reference 59

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source=pdf_text observed=2026-08-04T17:57:07.597560Z digest=sha256:26098c888309055a8899e95d05c3c2a033c9f0fa985009a36c413b217aac8a01

Observation 4ac6f411-6e0a-4277-8ee9-268c843c749f · outbound

This paper cites On the Taxonomy of De- velopers’ Discussion Topics with ChatGPT,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality On the Taxonomy of De- velopers’ Discussion Topics with ChatGPT,

Reference 60

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source=pdf_text observed=2026-08-04T17:57:07.600501Z digest=sha256:2569f514e5a3d2c6578577fee7ea932064e3416b475f603d9c5b537fbee1ba91

Observation facd4858-eba2-41c6-be2b-580971a34cd1 · outbound

This paper cites A cluster analysis method for grouping means in the analysis of variance,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality A cluster analysis method for grouping means in the analysis of variance,

Reference 61

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source=pdf_text observed=2026-08-04T17:57:07.603045Z digest=sha256:8d0fbf3b9b005169eeb88cd964bbd90170cd58ebd451cb3c0cab9f34a0831c90

Observation 5a879790-afaa-4a62-9b1a-ba5fa257aad2 · outbound

This paper cites Prompt engineering or fine-tuning: An empirical assessment of llms for code,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Prompt engineering or fine-tuning: An empirical assessment of llms for code,

Reference 62

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source=pdf_text observed=2026-08-04T17:57:07.605722Z digest=sha256:67731e9189a7cf26154d25e2e3629e0640988235f21e09ff0c0895d5c6d3f827

Observation dda21703-6b8a-4bd1-918c-bfd4527951bd · outbound

This paper cites Do code quality and style issues differ across (non-)machine learning notebooks? yes!.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Do code quality and style issues differ across (non-)machine learning notebooks? yes!

Reference 63

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source=pdf_text observed=2026-08-04T17:57:07.608605Z digest=sha256:bdad5880a177d8aefd830cb3913f276899d55ac5cd4ffc4b87d3be965cd05a53

Observation 0142b60e-ecf6-4bad-b801-478eb226abc0 · outbound

This paper cites Quality assessment of chatgpt generated code and their use by developers,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Quality assessment of chatgpt generated code and their use by developers,

Reference 64

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source=pdf_text observed=2026-08-04T17:57:07.611406Z digest=sha256:5d63ab06b37cd1f62923476f76884a7484db664d65e2532656f466a993a03a11

Observation 9d5a6086-0f39-4760-9242-6bb7cf15900f · outbound

This paper cites ChatGPT vs LLaMA: Impact, Reliability, and Challenges in Stack Overflow Discussions,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality ChatGPT vs LLaMA: Impact, Reliability, and Challenges in Stack Overflow Discussions,

Reference 65

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source=pdf_text observed=2026-08-04T17:57:07.613952Z digest=sha256:343ae8c3957e585eedb0c7bbfae7a5b36796365a1e10667188dec3dd1e6213f8

Observation 5dd7292c-b6ce-49cd-8c8c-d4d7ca583b1b · outbound

This paper cites Evaluating Source Code Quality with Large Language Models: a comparative study,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Evaluating Source Code Quality with Large Language Models: a comparative study,

Reference 66

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source=pdf_text observed=2026-08-04T17:57:07.616544Z digest=sha256:358e22624fd34fdcc63283577797ccfc83fe82e558253bbb12a58310983a740f

Observation 42d636d4-c141-4e82-96d6-3e1eaa242e62 · outbound

This paper cites Codechat repository,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Codechat repository,

Reference 67

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source=pdf_text observed=2026-08-04T17:57:07.619072Z digest=sha256:91ddcbbc0ba066de519c96fe518063a9e1d1f0cd879fc16fc2811dec13eaab02

Observation f43cfdba-45d1-4bd4-b1e7-72220ef7762d · outbound

This paper cites C4: contrastive cross-language code clone detection,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality C4: contrastive cross-language code clone detection,

Reference 68

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no resolver link, observed 2026-08-04T17:57:07.622009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:07.622009Z digest=sha256:2635cadad5f55034f852bfd35d355913f4d0ef96d8bdcad2200bdc6d712e41a7

Observation a40cca9b-9503-4365-beac-263be603abab · outbound

This paper cites Unveiling ChatGPT’s Usage in Open Source Projects: A Mining-based Study,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Unveiling ChatGPT’s Usage in Open Source Projects: A Mining-based Study,

Reference 69

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no resolver link, observed 2026-08-04T17:57:07.624659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:07.624659Z digest=sha256:39744ed0cb7d2ba9611de33fd3ba560ef6f417df3627527983cb2bf827dc112d

Observation 000b7457-c5dd-4bb2-893f-c1e898ec8f31 · outbound

This paper cites A Study of LLMs' Preferences for Libraries and Programming Languages.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality A Study of LLMs' Preferences for Libraries and Programming Languages

Reference 70

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no resolver link, observed 2026-08-04T17:57:07.627373Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:07.627373Z digest=sha256:0dd1d062d43d8f1d8527cffcb2ef5513e9aa907c049528bf7f4b210f5a86cf8d

Observation 5d781921-d737-4485-9b83-77fab8d0bbb3 · outbound

This paper cites Pep 8 – style guide for python code,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Pep 8 – style guide for python code,

Reference 71

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source=pdf_text observed=2026-08-04T17:57:07.630116Z digest=sha256:ea132ff1df5e599d5eb8bff2ee3d8a1448b81ab33a39f4261bb54389cb173470

Observation 3203096f-9bd7-49a5-951a-30c014fb8915 · outbound

This paper cites The kruskal-wallis test and stochastic homogeneity,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality The kruskal-wallis test and stochastic homogeneity,

Reference 72

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source=pdf_text observed=2026-08-04T17:57:07.632584Z digest=sha256:b774d01fcbbb69291bd0cff8e89e7c179b6662c9a3b38fd1b602f25b16df8305

Observation 3962afb9-a320-4f6e-b2bf-c8d8e82c51d0 · outbound

This paper cites Attention is All you Need,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Attention is All you Need,

Reference 73

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no resolver link, observed 2026-08-04T17:57:07.635300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:07.635300Z digest=sha256:2ff57dce034d95f1e526bb8c9080f3328b0910669ad9931a729f4c6377196286

Observation 6083d398-d711-46fc-acfc-a505a5b4ddb3 · outbound

This paper cites Cohen’s kappa coeffi- cient as a performance measure for feature selection,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Cohen’s kappa coeffi- cient as a performance measure for feature selection,

Reference 74

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no resolver link, observed 2026-08-04T17:57:07.637936Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:07.637936Z digest=sha256:c5107c790752a1c5e29f0bbedaceb9ff1df4aa60ce8153040f8ad4ff6b47c3cc

Observation 51484694-372e-4027-8986-f2c4663d4793 · outbound

This paper cites Wildchat: 1 million chatgpt interaction logs in the wild,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Wildchat: 1 million chatgpt interaction logs in the wild,

Reference 75

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no resolver link, observed 2026-08-04T17:57:07.640325Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:07.640325Z digest=sha256:ba3b20c03a61a35696c3729e2b095da2ac5e1327edb2938cf28e52170fd1edb5

Observation c88bda47-430b-4c48-b19b-a16473338966 · outbound

This paper cites Devgpt: Studying developer-chatgpt conversations,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Devgpt: Studying developer-chatgpt conversations,

Reference 76

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unresolved
no resolver link, observed 2026-08-04T17:57:07.642975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:07.642975Z digest=sha256:f7277e4d9396d59b4f398182a738201786cabbac6a5d3c49e250f6f80db00246

Observation 3f90c278-d590-47a4-82ef-834d00f8bbc4 · outbound

This paper cites Hacker news,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Hacker news,

Reference 77

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no resolver link, observed 2026-08-04T17:57:07.645484Z

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source=pdf_text observed=2026-08-04T17:57:07.645484Z digest=sha256:d04fb4a36ccbbd74705438cd2fc598ef16900e66721351f58da9ea4df7046163

Observation 7fc1cd91-f009-4f32-8727-4f6b74705df0 · outbound

This paper cites On Code Reuse from StackOverflow: An Exploratory Study on Jupyter Notebook.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality On Code Reuse from StackOverflow: An Exploratory Study on Jupyter Notebook

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-04T17:57:07.648260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:07.648260Z digest=sha256:8069ad27c2048431ce946833e9e7f26d65fb356f978cb5c5ea910c3748983fff

Observation 4cea8482-46d9-4710-9b15-17d65afbb11d · outbound

This paper cites A study of c/c++ code weaknesses on stack overflow,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality A study of c/c++ code weaknesses on stack overflow,

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-04T17:57:07.650964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:07.650964Z digest=sha256:a02a18c26644e87c4764b4c92d0ceb267f305e4d448ad851d4d35e169869a0e7

Observation 5f8834be-371b-49f6-8e43-f921765fbb87 · outbound

This paper cites WildChat: 1M ChatGPT Interaction Logs in the Wild.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality WildChat: 1M ChatGPT Interaction Logs in the Wild

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-04T17:57:07.653575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:07.653575Z digest=sha256:13f4ae0c69f34fdcdfcdebfaaf897bf578d812744ea0c96fe29a9ac4e74afe5e

Observation 54c6e2d0-3ba0-4a08-991e-f9b5024ae867 · outbound

This paper cites LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-04T17:57:07.656222Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T17:57:07.656222Z digest=sha256:042c7bf8603b4d1d628f70c8f6f2f3b4557407217caf0d64c1f495f35dacd9a0

Observation 56830864-8631-4c1d-aa0f-f4b23bf72361 · outbound

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

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality CodeGeeX: A Pre- Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X,

Reference 82

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unresolved
no resolver link, observed 2026-08-04T17:57:07.658902Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T17:57:07.658902Z digest=sha256:a38a8bf59680df958984478d066aafdafa876f29b7746d67c1c79dff8045cab1

Observation df280d2e-1e2d-4f81-ab94-934c7e334bfb · outbound

This paper cites Codechat,.

Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality Codechat,

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-04T17:57:07.661469Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T17:57:07.661469Z digest=sha256:b648445af252b311b68468071ea9d11f3f2df418489f04848ac79bfb6fd95ce1

Pith citing papers

Observation a12624ae-4fab-4e2c-a492-926043aec1ea · inbound

CodeChat-Eval: Evaluating Large Language Models in Multi-Turn Code Refinement Dialogues cites this paper.

CodeChat-Eval: Evaluating Large Language Models in Multi-Turn Code Refinement Dialogues Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-07-04T20:20:06.999588Z

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=2026-06-25T20:22:29.287534Z digest=sha256:a2eb1fa42155dd1a48208f18307f1dad482aa969eb6349cebfa4dfe080a222f1

Observation 5515df02-f1d1-445c-a293-1423a73087bd · inbound

CodeChat-Eval: Evaluating Large Language Models in Multi-Turn Code Refinement Dialogues cites this paper.

CodeChat-Eval: Evaluating Large Language Models in Multi-Turn Code Refinement Dialogues Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-07-01T08:55:35.342046Z

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=2026-07-01T07:05:50.811872Z digest=sha256:3949e0153718d9294b973fda0a2518620477c2879ec25390831c369e7bc767a9

Observation c061f352-6b77-417b-96f6-b4d0814e8f9c · inbound

From Human-Centric to Agentic Code Review: The Impact of Different Generations of Generative AI Technology on Review Quality cites this paper.

From Human-Centric to Agentic Code Review: The Impact of Different Generations of Generative AI Technology on Review Quality Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality

Reference 6

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no resolver link, observed 2026-08-02T05:59:02.657748Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-02T05:59:02.657748Z digest=sha256:4267407c54a83d7d30d302bb37405a94d2494ea603989936d2794e1cabbeb6db

Observation 084d18ae-e128-4560-bcb7-354e8287a16f · inbound

AdaptAgent: A Multi-agent, Domain-Guided Reasoning Framework for Code Adaptation cites this paper.

AdaptAgent: A Multi-agent, Domain-Guided Reasoning Framework for Code Adaptation Developer-LLM Conversations: An Empirical Study of Interactions and Generated Code Quality

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T23:51:02.423350Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:51:02.423350Z digest=sha256:28db7d9a98d8626c3c7ae480c52c23f93487b3ececb0de914e5dd155df28b0bd