Paper Citation Record · LEDGER

Comparing Human and LLM Generated Code: The Jury is Still Out!

As of 10 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 13 inbound Pith citation observations for arXiv:2501.16857.

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

pith.paper-citation-record.v1
2501.16857 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T10:11:10.939915Z

measured 53 of 53 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 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:18:37.494828Z

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

40 of 40 outbound references displayed

verified exact13
verified fuzzy12
unresolved15
parse uncertain0
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External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 3d51dc82-9531-4a95-82bd-d2869f6ffeb5 · outbound

This paper cites Devlin et al., ”BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,” in Proceedings of NAACL-HLT, 2019.

Comparing Human and LLM Generated Code: The Jury is Still Out! Devlin et al., ”BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,” in Proceedings of NAACL-HLT, 2019

Reference 1

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Observation 08d35321-8fc7-4a5a-9742-ec1908a9b040 · outbound

This paper cites Liawatimena et al., ”Django Web Framework Software Metrics Mea- surement Using Radon and Pylint,” in Journal of Physics: Conference Series, 2021.

Comparing Human and LLM Generated Code: The Jury is Still Out! Liawatimena et al., ”Django Web Framework Software Metrics Mea- surement Using Radon and Pylint,” in Journal of Physics: Conference Series, 2021

Reference 2

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Observation b54629f1-d59a-4545-8afb-9ba7adad55f7 · outbound

This paper cites Sharma and D.

Comparing Human and LLM Generated Code: The Jury is Still Out! Sharma and D

Reference 4

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Observation 6cfd1394-8597-41b3-bc88-b05c7eff3fa8 · outbound

This paper cites Jin et al., ”Software Code Quality Measurement: Implications from Metric Distributions,” in IEEE Transactions on Software Engineering, vol.

Comparing Human and LLM Generated Code: The Jury is Still Out! Jin et al., ”Software Code Quality Measurement: Implications from Metric Distributions,” in IEEE Transactions on Software Engineering, vol

Reference 5

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Observation 2fda2d46-1d97-4b1b-b27f-17d99318ba36 · outbound

This paper cites Ruohonen et al.

Comparing Human and LLM Generated Code: The Jury is Still Out! Ruohonen et al

Reference 6

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Observation 1db703f9-6742-48e9-a674-4d5013f57141 · outbound

This paper cites Feng et al.

Comparing Human and LLM Generated Code: The Jury is Still Out! Feng et al

Reference 7

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Observation 90ef5c30-f1b9-4f1b-9e8f-0cb0a1b344b2 · outbound

This paper cites Bias and Fairness in Large Language Models: A Survey.

Comparing Human and LLM Generated Code: The Jury is Still Out! Bias and Fairness in Large Language Models: A Survey

Reference 8

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This paper cites Yan et al., ”Practical and Ethical Challenges of Large Language Models in Education: A Systematic Scoping Review,” 2023.

Comparing Human and LLM Generated Code: The Jury is Still Out! Yan et al., ”Practical and Ethical Challenges of Large Language Models in Education: A Systematic Scoping Review,” 2023

Reference 9

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Observation 33756347-dc16-4f4d-816a-b45d416f4a6a · outbound

This paper cites A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT.

Comparing Human and LLM Generated Code: The Jury is Still Out! A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT

Reference 10

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Observation f78b9236-ba61-46ce-bb1d-21cdb6dd35c4 · outbound

This paper cites Correctness Comparison of ChatGPT-4, Gemini, Claude-3, and Copilot for Spatial Tasks.

Comparing Human and LLM Generated Code: The Jury is Still Out! Correctness Comparison of ChatGPT-4, Gemini, Claude-3, and Copilot for Spatial Tasks

Reference 11

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Observation c1cdb51d-8fc5-4859-a042-060a20535261 · outbound

This paper cites Chen et al., ”Capabilities of Large Language Models in Code Documentation,” 2024.

Comparing Human and LLM Generated Code: The Jury is Still Out! Chen et al., ”Capabilities of Large Language Models in Code Documentation,” 2024

Reference 12

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Observation fe453554-6dfe-496a-b34e-8897cfe4944b · outbound

This paper cites Ethical Considerations and Policy Implications for Large Language Models: Guiding Responsible Development and Deployment.

Comparing Human and LLM Generated Code: The Jury is Still Out! Ethical Considerations and Policy Implications for Large Language Models: Guiding Responsible Development and Deployment

Reference 13

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Observation 5cc4edb6-3467-4e47-b73f-616aa9219be0 · outbound

This paper cites Under the Surface: Tracking the Artifactuality of LLM-Generated Data.

Comparing Human and LLM Generated Code: The Jury is Still Out! Under the Surface: Tracking the Artifactuality of LLM-Generated Data

Reference 14

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Observation a576c29c-1eca-4e61-8f3c-2e809522edc3 · outbound

This paper cites Radford et al., ”Language Models are Few-Shot Learners,” in Advances in Neural Information Processing Systems, 2020.

Comparing Human and LLM Generated Code: The Jury is Still Out! Radford et al., ”Language Models are Few-Shot Learners,” in Advances in Neural Information Processing Systems, 2020

Reference 15

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Observation 56004d3e-1f96-4fe1-aa43-45215a9ca8b4 · outbound

This paper cites Tree of Thoughts: Deliberate Problem Solving with Large Language Models.

Comparing Human and LLM Generated Code: The Jury is Still Out! Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 16

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Observation 5482df19-561f-426c-9888-5a3efe4e4ca5 · outbound

This paper cites Evaluation of large language models for assessing code maintainability.

Comparing Human and LLM Generated Code: The Jury is Still Out! Evaluation of large language models for assessing code maintainability

Reference 17

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Observation 152ba950-8623-478d-81df-95fd4a38e152 · outbound

This paper cites Large Language Models for Code Analysis: Do LLMs Really Do Their Job?.

Comparing Human and LLM Generated Code: The Jury is Still Out! Large Language Models for Code Analysis: Do LLMs Really Do Their Job?

Reference 18

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This paper cites A Comparative Analysis of Large Language Models for Code Documentation Generation.

Comparing Human and LLM Generated Code: The Jury is Still Out! A Comparative Analysis of Large Language Models for Code Documentation Generation

Reference 19

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This paper cites Van Rossum et al.

Comparing Human and LLM Generated Code: The Jury is Still Out! Van Rossum et al

Reference 20

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Observation 460df4d8-30f6-4b90-8efc-bbc2eb97cc9c · outbound

This paper cites Du, et al.

Comparing Human and LLM Generated Code: The Jury is Still Out! Du, et al

Reference 21

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Observation 47e023df-6cbb-48a3-9fe1-2cb266e63894 · outbound

This paper cites Chang et al.

Comparing Human and LLM Generated Code: The Jury is Still Out! Chang et al

Reference 22

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Observation c0882ef6-5fec-47e6-8982-1e581dc33843 · outbound

This paper cites Ndukwe et al.

Comparing Human and LLM Generated Code: The Jury is Still Out! Ndukwe et al

Reference 23

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Comparing Human and LLM Generated Code: The Jury is Still Out! Unresolved cited work

Reference 24

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Observation 2d550fc2-b6d0-4191-b796-a411e94c728e · outbound

This paper cites Meldrum et al.

Comparing Human and LLM Generated Code: The Jury is Still Out! Meldrum et al

Reference 25

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Observation b5adcce7-0927-4521-9174-e07b40088c7f · outbound

This paper cites GPT-4 Technical Report.

Comparing Human and LLM Generated Code: The Jury is Still Out! GPT-4 Technical Report

Reference 26

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This paper cites Evaluating Large Language Models Trained on Code.

Comparing Human and LLM Generated Code: The Jury is Still Out! Evaluating Large Language Models Trained on Code

Reference 27

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Comparing Human and LLM Generated Code: The Jury is Still Out! Zolduoarrati et al

Reference 28

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Comparing Human and LLM Generated Code: The Jury is Still Out! Zolduoarrati and S

Reference 29

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Observation 9326328f-7c29-4228-8180-17e103f7a852 · outbound

This paper cites Barke et al.

Comparing Human and LLM Generated Code: The Jury is Still Out! Barke et al

Reference 30

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Comparing Human and LLM Generated Code: The Jury is Still Out! Tehrani et al

Reference 31

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Comparing Human and LLM Generated Code: The Jury is Still Out! Unresolved cited work

Reference 32

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This paper cites S., Wang, Y ., and Zhang, L.

Comparing Human and LLM Generated Code: The Jury is Still Out! S., Wang, Y ., and Zhang, L

Reference 33

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Comparing Human and LLM Generated Code: The Jury is Still Out! Unresolved cited work

Reference 34

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Comparing Human and LLM Generated Code: The Jury is Still Out! CodeBLEU: a Method for Automatic Evaluation of Code Synthesis

Reference 35

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Comparing Human and LLM Generated Code: The Jury is Still Out! Unresolved cited work

Reference 36

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Comparing Human and LLM Generated Code: The Jury is Still Out! N., Denny, P., Becker, B

Reference 37

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This paper cites Large Language Models as Robust Data Generators in Software Analytics: Are We There Yet?.

Comparing Human and LLM Generated Code: The Jury is Still Out! Large Language Models as Robust Data Generators in Software Analytics: Are We There Yet?

Reference 38

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Comparing Human and LLM Generated Code: The Jury is Still Out! Unresolved cited work

Reference 39

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Comparing Human and LLM Generated Code: The Jury is Still Out! Optimizing Large Language Model Hyperparameters for Code Generation

Reference 40

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This paper cites ACM Transactions on Computer-Human Interaction, 31, 1, Article 1 (January 2024), 35 pages.

Comparing Human and LLM Generated Code: The Jury is Still Out! ACM Transactions on Computer-Human Interaction, 31, 1, Article 1 (January 2024), 35 pages

Reference 2023

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Pith citing papers

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Understanding Automated Program Repair Agents Through the Lens of Traceability: An Empirical Study cites this paper.

Understanding Automated Program Repair Agents Through the Lens of Traceability: An Empirical Study Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 25

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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 Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 13

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An Evaluation of Large Language Models for Detection of Malicious Python Packages cites this paper.

An Evaluation of Large Language Models for Detection of Malicious Python Packages Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 57

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Do AI Coding Agents Log Like Humans? An Empirical Study cites this paper.

Do AI Coding Agents Log Like Humans? An Empirical Study Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 17

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Observation f755d1a5-18bf-4cb6-aefe-026e34873e7d · inbound

To What Extent Does Agent-generated Code Require Maintenance? An Empirical Study cites this paper.

To What Extent Does Agent-generated Code Require Maintenance? An Empirical Study Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 16

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To What Extent Does Agent-generated Code Require Maintenance? An Empirical Study cites this paper.

To What Extent Does Agent-generated Code Require Maintenance? An Empirical Study Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 16

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Characterizing Readability Issue Patterns and the Role of Prompt Design in LLM-Generated Code cites this paper.

Characterizing Readability Issue Patterns and the Role of Prompt Design in LLM-Generated Code Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 57

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Characterizing Readability Issue Patterns and the Role of Prompt Design in LLM-Generated Code cites this paper.

Characterizing Readability Issue Patterns and the Role of Prompt Design in LLM-Generated Code Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 52

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Can LLMs Produce Better Object-Oriented Designs than Human-Involved Development? cites this paper.

Can LLMs Produce Better Object-Oriented Designs than Human-Involved Development? Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 8

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Observation d4130318-d011-4b9b-9aca-6f4d06f900b9 · inbound

At What Cost? Software Developers' Well-Being in the Age of GenAI cites this paper.

At What Cost? Software Developers' Well-Being in the Age of GenAI Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 12

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How to Compare the Security of Code Written by Humans to LLM-generated Code cites this paper.

How to Compare the Security of Code Written by Humans to LLM-generated Code Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-06-28T21:42:39.501625Z

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Observation aab2e7a5-2dd8-442a-bb0b-3a57bc2cbec0 · inbound

How to Compare the Security of Code Written by Humans to LLM-generated Code cites this paper.

How to Compare the Security of Code Written by Humans to LLM-generated Code Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-07-01T07:45:28.813832Z

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 1c41d156-96b9-4dd5-9df1-d08f354b37fd · inbound

AIP: A Graph Representation for Learning and Governing Agent Skills cites this paper.

AIP: A Graph Representation for Learning and Governing Agent Skills Comparing Human and LLM Generated Code: The Jury is Still Out!

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T08:36:47.763287Z

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.