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Paper Citation Record · LEDGER

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT

As of 22 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 9 inbound Pith citation observations for arXiv:2502.17450.

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

pith.paper-citation-record.v1
2502.17450 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:11:39.249954Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T18:56:33.898465Z

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

26 of 26 outbound references displayed

  • verified exact2
  • verified fuzzy19
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation d5fe2801-d5bf-4d44-a51d-71698033cd31 · outbound

This paper cites GitHub Copilot,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT GitHub Copilot,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.895587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.087832Z digest=sha256:17abe5f11ed0787b8e6a4c20303a6cadb42b72493953084378da5e66c272431d

Observation 33bf0a8e-2ed0-4973-9b6a-266a2108d5ba · outbound

This paper cites Visual Studio Code,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Visual Studio Code,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.879151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.102443Z digest=sha256:5efb3858cb8bfcef457b0e1579b6828a9390cd0143122555e41f4eae404f9d0f

Observation 657c5780-e0f4-4d7c-b2da-a559e7622a4c · outbound

This paper cites ChatGPT,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT ChatGPT,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.862427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.108443Z digest=sha256:2cf430c11e375b2bf56cd903172c7714084a04e1019520ee8b71e061d8079dc0

Observation ae2a1675-f088-49f2-baf9-54697fca2d58 · outbound

This paper cites an unresolved cited work.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-08T20:11:39.843430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.114328Z digest=sha256:1fd7499466a305cc1802f47d96f130238f8b4fd736b69fd12d9722a483af1ea5

Observation 366292d6-7db0-4cc3-9db9-e78832d5aa4e · outbound

This paper cites CodeGPT,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT CodeGPT,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.825983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.121034Z digest=sha256:8ea6626dae71fb69217b0c95a50b24daf0e96a080f9414404a05a87e67127971

Observation 88bad5a4-395a-456b-b388-3eaab8fff887 · outbound

This paper cites Eclips Gemini,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Eclips Gemini,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.807775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.126763Z digest=sha256:fe05a131d4ce822c27cb2c661dcdefcf414cd2eff974b19583136cfd38440b65

Observation c3ebc37e-3f80-4234-a68f-b601774e4d28 · outbound

This paper cites Generating Java Methods: An Empirical Assessment of Four AI-Based Code Assistants,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Generating Java Methods: An Empirical Assessment of Four AI-Based Code Assistants,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.787303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.132637Z digest=sha256:e2a91b28d3c9360c462e306ef1611fea68de542e4e564539b51a0481e1aeb9b7

Observation eb50d517-f6dd-4b67-9930-4e4cb69e9b1a · outbound

This paper cites Developer Experiences with a Contextualized AI Coding Assistant: Usability, Expectations, and Outcomes,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Developer Experiences with a Contextualized AI Coding Assistant: Usability, Expectations, and Outcomes,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.765775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.139231Z digest=sha256:60271406425326d281025edd6c779cd741fdc4d316a61e535f97e9c202d2d238

Observation 28420850-ed1e-4156-82cf-615d8f56248d · outbound

This paper cites A large-scale survey on the usability of ai programming assistants: Successes and challenges,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT A large-scale survey on the usability of ai programming assistants: Successes and challenges,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.746438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.148619Z digest=sha256:1959693232600946e1c8d8476b84dd5f095c1847a65854e731d76410eeacd0e9

Observation 5a4c406d-cddd-4ad9-a55e-5fc19b940ec9 · outbound

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

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Unveiling ChatGPT’s Usage in Open Source Projects: A Mining-based Study,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.721411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.154867Z digest=sha256:fa71d1e33262797f5fec1623d08bac3257cc3cab4d861663b9c267e2cbeb4585

Observation a97093a6-da08-4f62-a8ac-3e016aef588b · outbound

This paper cites Extending the frontier of ChatGPT: Code generation and debugging,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Extending the frontier of ChatGPT: Code generation and debugging,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.698104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.161172Z digest=sha256:7afcff77b653ef2b6022a01a4a67a34d7aa1401c653e5ae21f0f57b950295c44

Observation 3066af6e-6ddf-468b-9078-89f578d321f1 · outbound

This paper cites Quality Assessment of ChatGPT Generated Code and their Use by Developers,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Quality Assessment of ChatGPT Generated Code and their Use by Developers,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.674985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.167256Z digest=sha256:2008b417260b07cdc8ca4fb3710618dc2b10375cdc8f6907dee0aff1d88f80cd

Observation 50f6817e-502a-4989-bfa7-48976f931482 · outbound

This paper cites Self-Collaboration Code Gener- ation via ChatGPT,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Self-Collaboration Code Gener- ation via ChatGPT,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.654009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.173844Z digest=sha256:d333caa0076db997fb13fbb6f6b53aadc70207648823f90eb113bb41b8c1bdff

Observation fe8e3c3b-c728-453c-827d-bc8541ed38d2 · outbound

This paper cites Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.632718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.179332Z digest=sha256:387f81eca65357de89d1c91c977a6584758cbb3b261e59d6508ffe38763ad467

Observation 2783886c-ad60-4cac-8d7f-32f5108eaad9 · outbound

This paper cites Optimizing Large Language Model Hyperparameters for Code Generation.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Optimizing Large Language Model Hyperparameters for Code Generation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-08T20:11:39.185448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:11:39.185448Z digest=sha256:636421882e606e5284189f5c6458b501048b7bb2f7e6861a51022be30c9e174e

Observation 06078548-2a47-4c01-bedb-773b1e205877 · outbound

This paper cites Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-08T20:11:39.191448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:11:39.191448Z digest=sha256:f77edd58fc2189355857806c25da2ec07b85bd3a4262300007b69283017d4d6f

Observation 94d5d1da-7480-4d63-8332-4ea0135542d4 · outbound

This paper cites An Empirical Study of the Non-determinism of ChatGPT in Code Generation,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT An Empirical Study of the Non-determinism of ChatGPT in Code Generation,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.599634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.196599Z digest=sha256:6380b580d8701e92a130f060d8651314ac58dd82313c4bb59b4a08ee236a7ebb

Observation 13ab9311-6275-42c9-aee8-52cc4d3baaf3 · outbound

This paper cites Most used AI search and developer tools among developers worldwide 2024,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Most used AI search and developer tools among developers worldwide 2024,

Reference 18

Resolution
verified exact
raw_fallback, observed 2026-08-08T20:11:39.464165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.201856Z digest=sha256:2cd1c481efc6a8aee6d165f0ce17c40ad986bf0783e1d43f744a4da2e4a623e8

Observation 8d02904c-9c5b-4ce1-aaae-b770cbdaf19a · outbound

This paper cites The Curious Case of Neural TExt Degeneration,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT The Curious Case of Neural TExt Degeneration,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.580380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.208552Z digest=sha256:7304f66487a6e7ddb385efdde0d487f6583db17c8f400a768692762618f63f98

Observation 8dfdf977-58d9-4c06-9e17-9983ba25cf90 · outbound

This paper cites Top Pass: Improve Code Generation by Pass@k-Maximized Code Ranking.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Top Pass: Improve Code Generation by Pass@k-Maximized Code Ranking

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-08T20:11:39.347286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.215550Z digest=sha256:8a6706d80aa2f890d45efca4ec789a049aac95417c545ad0de722a0ecd224466

Observation 94b8ebf9-25eb-439e-9076-b4ba834b1306 · outbound

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

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT A Survey on Evaluating Large Language Models in Code Generation Tasks

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-08T20:11:39.222174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:11:39.222174Z digest=sha256:0273c505f042003efc67e0e93f6d6f0827d565aa4716e3bf4a2a4e9c625ee29c

Observation c2db2388-0c37-4ea9-8384-5ccc68571de2 · outbound

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

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT A Survey on Large Language Models for Code Generation

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-08T20:11:39.228004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T20:11:39.228004Z digest=sha256:51a8b44564e6dfc594d245ed53e95d4246117b7be547bf0c3ec0f9db3f8a3399

Observation fc0bcaf8-501a-444a-90d5-9ed9e1255b41 · outbound

This paper cites Analyzing Prompt Influence on Automated Method Generation: An Empirical Study with Copilot,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Analyzing Prompt Influence on Automated Method Generation: An Empirical Study with Copilot,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.559125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.233936Z digest=sha256:1fae044d741bb1195dad3d52f00c162c476d85dc6f5e956304185784e89dd0f5

Observation f206a61d-1534-421d-9b2a-cee07523703a · outbound

This paper cites Using AI-based coding assistants in practice: State of affairs, perceptions, and ways forward,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Using AI-based coding assistants in practice: State of affairs, perceptions, and ways forward,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.542164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.239117Z digest=sha256:ebac4a3761ed76ca5262c5f901522e9845a6e920308be5132465515f777d6b08

Observation f4f7b24f-5485-43f4-a498-1520d722f53e · outbound

This paper cites Can LLMs Facilitate Onboarding Software Developers? An Ongoing Industrial Case Study,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Can LLMs Facilitate Onboarding Software Developers? An Ongoing Industrial Case Study,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.524494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.244809Z digest=sha256:594dd7aedc09aa3da17e24f6353308290a415f4feb0d5235c0c7011d0cbfd1a3

Observation 029d6525-07b5-4f40-8ec0-9f0e0e4d422f · outbound

This paper cites Large Language Models for Software Engineer- ing: Survey and Open Problems,.

Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT Large Language Models for Software Engineer- ing: Survey and Open Problems,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:11:39.505286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-08T20:11:39.249954Z digest=sha256:1c3edb97403d5fe6d4096da2f367ab040840f29c0e5e0d0d6214de2cd6239ebc

Pith citing papers

Observation 196fddc8-265a-466d-b5a2-60794d4a4c21 · inbound

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

A Study of LLMs' Preferences for Libraries and Programming Languages Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-22T22:55:12.186267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-22T22:53:16.951417Z digest=sha256:29c70b6e23cd5bd512d70a088fe8ae81c6d58dd81adb15b575c7143b69d9dc0a

Observation f200ecae-5df6-45ec-a267-4c7052fe9f11 · inbound

Library Hallucinations in LLM-Generated Code: A Risk Analysis Grounded in Developer Queries cites this paper.

Library Hallucinations in LLM-Generated Code: A Risk Analysis Grounded in Developer Queries Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-21T22:34:23.701950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-05-21T22:31:20.358758Z digest=sha256:06012e8989987b9effd6353c5d85b115886acd9d6e96287194ebe15aa684121a

Observation 8863edf8-542c-4f66-8b79-1e08a2cb68ad · inbound

Context-Guided Decompilation: A Step Towards Re-executability cites this paper.

Context-Guided Decompilation: A Step Towards Re-executability Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:35:36.440363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T01:33:54.870931Z digest=sha256:381a614a42cbc60b65e3d73af3b2c55acb6b1f432073494fef1985dc67b85b17

Observation c0a5cddf-b0f7-4703-a5f4-187656e6e74d · inbound

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code cites this paper.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-04T06:49:06.377877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:06.377877Z digest=sha256:8a244f080827f42b5eebecc1ad65487a7c35bfa82a0cf244824b483a7de17107

Observation 4226123d-9f10-4999-90a7-17c4cfbabb76 · inbound

Dataset-Level Metrics Attenuate Non-Determinism: A Fine-Grained Non-Determinism Evaluation in Diffusion Language Models cites this paper.

Dataset-Level Metrics Attenuate Non-Determinism: A Fine-Grained Non-Determinism Evaluation in Diffusion Language Models Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:35:26.443083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T13:31:46.940449Z digest=sha256:1c4157881ce31332d159d2296675489bb9dbbf8ec113d7ea8f49794d86a5c221

Observation b0f16067-7348-4102-ae33-3b856e147c7f · inbound

DF3DV-1K: A Large-Scale Dataset and Benchmark for Distractor-Free Novel View Synthesis cites this paper.

DF3DV-1K: A Large-Scale Dataset and Benchmark for Distractor-Free Novel View Synthesis Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-12T20:50:53.567415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T20:50:53.567415Z digest=sha256:39f0649b8681f8c4672c3101b7a79fcb1cb8d079a80e1fc7893894b52192f1c9

Observation dfc7275f-03c9-4576-a8c0-d1a9724cf640 · inbound

The Illusion of Safety: Multi-Tier Verification of AI vs. Human C++ Code cites this paper.

The Illusion of Safety: Multi-Tier Verification of AI vs. Human C++ Code Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT

Reference 42

Resolution
unresolved
no resolver link, observed 2026-07-12T09:44:42.646014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T09:44:42.646014Z digest=sha256:77bd883c9e27571c4dc726480085e60a5658212c6be18cee62cfb54e6477d610

Observation b037181c-4fab-43c6-9882-6746b42de7fd · inbound

The Illusion of Safety: Multi-Tier Verification of AI vs. Human C++ Code cites this paper.

The Illusion of Safety: Multi-Tier Verification of AI vs. Human C++ Code Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT

Reference 42

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no resolver link, observed 2026-08-04T04:38:08.200644Z

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source=pdf_text observed=2026-08-04T04:38:08.200644Z digest=sha256:70f5878b5e29d9052d604cab6896042bbece99a31c01729f4c9c1fd005c95148

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LangChoiceBench: Measuring and Explaining Programming-Language Choice in LLMs cites this paper.

LangChoiceBench: Measuring and Explaining Programming-Language Choice in LLMs Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT

Reference 2

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source=arxiv_source observed=2026-08-07T18:56:33.898465Z digest=sha256:758f1bc9791188e412430ee163f1cb412d41de6a2bc384942f9b66aa8a3ed08d