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Paper Citation Record · LEDGER

Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:2304.10778.

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

pith.paper-citation-record.v1
2304.10778 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:01:10.524442Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

68
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a3f13fc8-8b45-49ed-bace-4b3494f1e763 · inbound

Assessing, Exploiting, and Mitigating Syntactic Robustness Failures in LLM-Based Code Generation cites this paper.

Assessing, Exploiting, and Mitigating Syntactic Robustness Failures in LLM-Based Code Generation Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-24T02:23:46.135108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-24T02:19:23.135463Z digest=sha256:6c286f4fda36a73f5d18dd095b5c914b48f444234964c179b25fdb896e5b0ace

Observation 782a917c-c3f4-4d76-9ec9-3bc0aad8c8bc · inbound

Large Language Model-Based Agents for Software Engineering: A Survey cites this paper.

Large Language Model-Based Agents for Software Engineering: A Survey Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-17T12:35:48.586291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T12:35:48.170947Z digest=sha256:06b8ec1f4b590bc85fd872767c6b9f653ff4fdb7af3a32560d5239d199c866ce

Observation 2370909f-31e6-49eb-bdfa-c3d92dcf1b73 · inbound

Eradicating the Unseen: Detecting, Exploiting, and Remediating a Path Traversal Vulnerability across GitHub cites this paper.

Eradicating the Unseen: Detecting, Exploiting, and Remediating a Path Traversal Vulnerability across GitHub Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 125

Resolution
unresolved
no resolver link, observed 2026-08-07T14:01:10.524442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:01:10.524442Z digest=sha256:5188e2d63be4714b31c92bd2139804bc7d8ee468c2a28c056f304e8307886f04

Observation ea630df8-ea98-478a-a14c-c569e096c2dd · inbound

Do Generative AI Tools Ensure Green Code? An Investigative Study cites this paper.

Do Generative AI Tools Ensure Green Code? An Investigative Study Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T05:04:38.131274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:04:38.131274Z digest=sha256:71420144344d06b3f5b93e5658cd403e2885075d5c07b907668715b6a8669587

Observation 9da3e49d-a12e-44d9-b41c-d7f49378169f · inbound

Quality Assessment of Python Tests Generated by Large Language Models cites this paper.

Quality Assessment of Python Tests Generated by Large Language Models Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T00:22:57.143131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:22:57.143131Z digest=sha256:04ad71438c8d3c6804653107f401a8a959035db8eff4eb4b3ef532080a9c22b5

Observation 47f5486b-76b8-41db-82a6-80dd5d887dcf · inbound

Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis cites this paper.

Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:34.032611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:09:34.032611Z digest=sha256:81b8615a408e36c2b76fe52a8a46a38d4d879f2c58aa37d49c537992e01d9c70

Observation 0aed5b4b-8f70-4b6c-b77e-b74404cbfc73 · inbound

Is Quantization a Deal-breaker? Empirical Insights from Large Code Models cites this paper.

Is Quantization a Deal-breaker? Empirical Insights from Large Code Models Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T17:56:21.332123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:56:21.332123Z digest=sha256:ce7fccc88926ccc051974383317ca63ffe63d82cfa07d9c8ee6731ff60cc822a

Observation 72ecfa1c-470b-4af0-b922-86c1d5712d6f · inbound

Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity cites this paper.

Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T14:09:55.151998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:09:55.151998Z digest=sha256:a73fe7092c8fae3d7ae8d69ffd14d0cf9fad84782ff96a32602dd348c07b65ee

Observation 91397d05-6cc8-4774-b395-391f63d70582 · inbound

Secure Code Generation at Scale with Reflexion cites this paper.

Secure Code Generation at Scale with Reflexion Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-03T23:50:48.870152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T23:50:48.870152Z digest=sha256:5dbccd0c583c7427375535d905e8878ec30f40c5555cbd39f66d8d8953f3deeb

Observation d95378ad-5796-4592-8880-21dcebda23d0 · inbound

WildCode Revisited: A Comprehensive Empirical Study on the Security of LLM-Generated Code cites this paper.

WildCode Revisited: A Comprehensive Empirical Study on the Security of LLM-Generated Code Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-03T18:41:21.046690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:41:21.046690Z digest=sha256:912b877cde057ca5fcd775e0b8fb51f08d684daff0553cca168965f6b91a98bd

Observation 1c457c1b-075d-42b7-b2cf-100f5fae9515 · inbound

Developers' Experience with Generative AI -- First Insights from an Empirical Mixed-Methods Field Study cites this paper.

Developers' Experience with Generative AI -- First Insights from an Empirical Mixed-Methods Field Study Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-03T14:36:05.053801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:36:05.053801Z digest=sha256:47d534dbe1d2b5d6d33573c2b7ce9bdcbd7077cb58f4e1f780a3658f0b12f176

Observation 5a65d466-b3a8-46ed-84be-a43604fa4358 · inbound

Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents cites this paper.

Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-15T12:25:35.816573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T12:22:13.551709Z digest=sha256:fd1388f165d4a05a1e9b28c0ac0c2500849d8ac780ded829a9461e9f658b5b5e

Observation abf424bd-55fa-4884-b37c-d915692abc33 · inbound

How Do Developers Interact with AI? An Exploratory Study on Modeling Developer Programming Behavior cites this paper.

How Do Developers Interact with AI? An Exploratory Study on Modeling Developer Programming Behavior Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-14T22:13:03.187010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T22:12:39.662344Z digest=sha256:c1f21f89ec3456bcb1074569a5ad965d7ab2f4c3727057c804ebe847aab9ed69

Observation 5d8d6985-83c1-4851-a97a-189ba6c69d82 · inbound

A Longitudinal Analysis of Good First Issue Practices and Newcomer Pull Requests in Popular OSS Projects cites this paper.

A Longitudinal Analysis of Good First Issue Practices and Newcomer Pull Requests in Popular OSS Projects Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:36:26.359139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T10:22:16.502977Z digest=sha256:aca0eeeffc52d706d4cebc54914425f46eff05d4201d91959d22964f45b5e1ab

Observation 42380031-75ce-46a2-9cdd-a3dd7dc4a604 · inbound

Social Bias in LLM-Generated Code: Benchmark and Mitigation cites this paper.

Social Bias in LLM-Generated Code: Benchmark and Mitigation Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 166

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:36:08.664051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-09T19:34:51.433422Z digest=sha256:6c1e43506afde1c3136d7ad3b0f5c8b5ef220f396ac9c1a7341bceb66ba3c50c

Observation ead6af44-bc68-49ed-b57b-2252c5cad799 · inbound

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code cites this paper.

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 144

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:26:04.532845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T17:37:51.790000Z digest=sha256:cdb03c2a36bed368fe0fd0952d799cf181cfe873f48226561ae072810390cda7

Observation a7e81a2c-790a-406d-b2cc-8247207dc878 · inbound

Context-Augmented Code Generation: How Product Context Improves AI Coding Agent Decision Compliance by 49% cites this paper.

Context-Augmented Code Generation: How Product Context Improves AI Coding Agent Decision Compliance by 49% Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:51:48.713785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T01:33:26.870356Z digest=sha256:fc64407a5037f1a97249d30748218b645a771ac8877785b415283097915cdb97

Observation 5b736f39-a10e-49b4-8e67-e53a712126ca · inbound

LLM Translation of Compiler Intermediate Representation cites this paper.

LLM Translation of Compiler Intermediate Representation Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:36:23.986923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T00:59:05.006846Z digest=sha256:a3c821060efd9823985f9cf47edb27b0ac04216d214a265e229e06ec1656da73

Observation 7160c5ee-8e62-4740-b672-920004c215c2 · inbound

Revisiting DAgger in the Era of LLM-Agents cites this paper.

Revisiting DAgger in the Era of LLM-Agents Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-14T19:57:53.334730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T19:56:06.762156Z digest=sha256:394cdca35aa353d68e9cf16399566a8ace4e3efccab764357c717b34fc6cea27

Observation 02c7bacd-5822-4fd3-90c3-0749139f913a · inbound

Assistance to Autonomy: A Systematic Literature Review of Agentic AI across the Software Development Life Cycle cites this paper.

Assistance to Autonomy: A Systematic Literature Review of Agentic AI across the Software Development Life Cycle Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-19T16:27:39.536761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T16:27:05.280664Z digest=sha256:cce3a191ee0c56522d46def2ed125f7e7897fb42924e843378c55460116c9d52

Observation e2bf9ea6-586b-497d-820a-3056a6e9cfc3 · inbound

The Impact of AI Coding Assistants on Software Engineering: A Longitudinal Study cites this paper.

The Impact of AI Coding Assistants on Software Engineering: A Longitudinal Study Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 52

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verified exact
arxiv_id, observed 2026-05-25T04:10:19.405479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T04:09:32.859538Z digest=sha256:a897a02d59ba4b145dd646b5e28b5fea94df2c6455999e282333b6b15914e06e

Observation 0d790177-c688-46f4-a823-bb8c71da0c47 · inbound

An Empirical Evaluation of LLM-Generated Code Security Across Prompting Methods cites this paper.

An Empirical Evaluation of LLM-Generated Code Security Across Prompting Methods Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 45

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T15:34:48.545994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-30T15:17:26.306332Z digest=sha256:9bdf801eec37c0ba1c196a02151577ef7776471ad7c6242027b40ce029da9d45

Observation b495116f-2720-4b29-96ff-d75ee996fcb3 · inbound

Enhancing Reliability in LLM-Based Secure Code Generation cites this paper.

Enhancing Reliability in LLM-Based Secure Code Generation Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-06-30T15:14:46.819405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T15:14:02.156588Z digest=sha256:50afc8ae3a6990c7f24a0bf4991949257b1085f095063d73fbb02266d402fb05

Observation 0983d97b-a03b-4077-8ef8-139e3dbfb646 · inbound

From Prompting to Verification: How Experience Shapes Vibe Coding Practices cites this paper.

From Prompting to Verification: How Experience Shapes Vibe Coding Practices Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 79

Resolution
verified exact
arxiv_id, observed 2026-06-30T13:14:40.443345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T13:13:31.583222Z digest=sha256:268be1607e06bd26c781c6fd56d784b58277c15ad684c1d234ba8eb2add17021

Observation 4f993f05-eb35-474b-bf78-30c27b9efe2d · inbound

Short-Term Gain, Long-Term Fragility: AI Labor Substitution and the Erosion of Sustainable Capability cites this paper.

Short-Term Gain, Long-Term Fragility: AI Labor Substitution and the Erosion of Sustainable Capability Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-05T01:40:34.395921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-05T01:39:02.068361Z digest=sha256:ef305ec8e37dd662bd42770dbd09f03b394f70f360654d44bd46ddc62bea8f75

Observation ecdfa141-efee-49c2-badf-100bc1cf27ca · inbound

Vibe Coding Ate My Homework: An evaluation of AI approaches to greenfield software engineering and programming cites this paper.

Vibe Coding Ate My Homework: An evaluation of AI approaches to greenfield software engineering and programming Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-03T18:38:49.553754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T02:38:26.858639Z digest=sha256:d9c31db29bad1f52ff83a87d52e0f5bb2e79b0d3adca13e8fe3009ebb76a1ff4

Observation 10083c92-43cd-4d7a-a759-65aaaf1704b3 · inbound

Vibe Coding Ate My Homework: An evaluation of AI approaches to greenfield software engineering and programming cites this paper.

Vibe Coding Ate My Homework: An evaluation of AI approaches to greenfield software engineering and programming Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:37:25.387141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-02T22:33:44.537174Z digest=sha256:640867b7b2d3e51209664a1fab3d97a2f9986facb8df769700fc09b66b34f9c0

Observation e2387973-e3f3-4570-a290-88635a207d13 · inbound

Qiskit Code Migration with LLMs cites this paper.

Qiskit Code Migration with LLMs Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-06-26T16:29:35.520168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T16:24:25.357338Z digest=sha256:8c5b9a6e525959e632a2b0ee3c8119e0f73e0bee4bf63e771ece3db78e7114ff

Observation fa765d41-fe23-4f25-96b0-f5887e7e8317 · inbound

Quantize with Confidence? An Empirical Study of Quantization for Code Generation cites this paper.

Quantize with Confidence? An Empirical Study of Quantization for Code Generation Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-02T03:32:48.904884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T03:32:48.904884Z digest=sha256:acb6178dcb9df0cd6d2a8b164d6752aaf6b4cc0e0db5e9c72c8376ff25ee82d8

Observation 76c3128b-b8f6-491f-9044-1975539ba6d2 · inbound

Large Language Models for Code Generation from Multilingual Prompts: A Curated Benchmark and a Study on Code Quality cites this paper.

Large Language Models for Code Generation from Multilingual Prompts: A Curated Benchmark and a Study on Code Quality Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 105

Resolution
unresolved
no resolver link, observed 2026-08-02T01:01:33.546349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T01:01:33.546349Z digest=sha256:11a07d9d7f36595335972201e1d6070f9effbd452dcccb8da329591443c6d144

Observation 37fff69e-d8b3-448c-b348-27515ea2e447 · inbound

Design Theater: Evaluating the Gap Between User-Facing Design Reasoning and Implementation in Generative UI Tools cites this paper.

Design Theater: Evaluating the Gap Between User-Facing Design Reasoning and Implementation in Generative UI Tools Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-01T04:11:14.979264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T04:11:14.979264Z digest=sha256:8751242fdbf843a296158db80f18ea9aa9139379a89f22501dd68bc253b76719

Observation 6769482c-be19-4780-91d9-39d203be9dd1 · inbound

Design Theater: Evaluating the Gap Between User-Facing Design Reasoning and Implementation in Generative UI Tools cites this paper.

Design Theater: Evaluating the Gap Between User-Facing Design Reasoning and Implementation in Generative UI Tools Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-04T01:35:39.591608Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-04T01:35:39.591608Z digest=sha256:3ec2d3bb660760c8bd91a0b53b0f29afad07f63499a5b10e984ed587e85732a1