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Paper Citation Record · LEDGER

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code

As of 10 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 2 inbound Pith citation observations for arXiv:2511.15817.

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

pith.paper-citation-record.v1
2511.15817 v6

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T06:49:11.634098Z

measured 55 of 55 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-13T05:58:41.120953Z

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

53 of 53 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved47
  • parse uncertain0
  • malformed identifier4
  • metadata mismatch0

External citation measurements

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

Outbound references

Observation cb702348-944a-4c89-bfd9-721cbd88cbe8 · outbound

This paper cites Few-shot training LLMs for project-specific code-summarization.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Few-shot training LLMs for project-specific code-summarization

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:05.744943Z digest=sha256:5d8987f65617ecccadb3bad5b7dd8041f86d5ea8b9cc3d1cf1ba341c79b800f4

Observation d650bd45-2e30-49fc-b206-e3a2285c70fd · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 2

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source=pdf_text observed=2026-08-04T06:49:05.839484Z digest=sha256:7e7cf026040b9ae18df6c1cfea9c1f4316f05e2adf80c517181dbc7a26e7caae

Observation 138fa5c1-d6a4-431d-ab88-de3499341580 · outbound

This paper cites Sampling in Software Engineering Research: A Critical Review and Guidelines.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Sampling in Software Engineering Research: A Critical Review and Guidelines

Reference 3

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source=pdf_text observed=2026-08-04T06:49:05.934693Z digest=sha256:9b55a63702d8d68f15850d8255a6351a194a8778a99aac264044638241d66175

Observation c7bb6058-f4cb-4fcb-bd98-6da99acada42 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Evaluating Large Language Models Trained on Code

Reference 4

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:06.046598Z digest=sha256:6e6b49c9e1d6d8f2b389e1dee08306288f9a313b47bbd4b2688f9fdb1f6c5e84

Observation be03a724-b283-4671-a6ea-6c1e69393531 · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 5

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no resolver link, observed 2026-08-04T06:49:06.141854Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:06.141854Z digest=sha256:f96bd16a14878f100525f5bab8912490dc2d75cd7d46bc7416a063ba7b97b15d

Observation cf12001a-18b9-4ff5-8b95-a57ccb5b2089 · outbound

This paper cites Cruzes and Tore Dyba.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Cruzes and Tore Dyba

Reference 6

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no resolver link, observed 2026-08-04T06:49:06.200602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:06.200602Z digest=sha256:29c96fc465c345444bc7fc55411cdd5215f438eb1ad42a478cdbc41efff5d578

Observation e7c5ddab-0e77-4469-997a-0469a72c7afc · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 7

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source=pdf_text observed=2026-08-04T06:49:06.266463Z digest=sha256:6927b87054e405e912d4a8be75c1bd2ff17273f684206fb3cfc3f4723bfc3124

Observation 547cfa6c-28e8-40b7-9458-c5b0dbea8b33 · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 8

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source=pdf_text observed=2026-08-04T06:49:06.474559Z digest=sha256:76e023807602ce6213e1c46e51f61113df841de38083bd110342f9c93730652c

Observation f779a184-ed4f-41b7-b75c-9a1f27cc7cc0 · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 9

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verified exact
doi, observed 2026-08-04T06:53:26.493409Z

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.

source=pdf_text observed=2026-08-04T06:49:06.691937Z digest=sha256:dfa125f816a86d6dcd3244a73f6aa5c2f903c04feb6665576141378e01fc5b6c

Observation 8adce556-0857-474e-9905-325800aedbd4 · outbound

This paper cites Mistral 7B.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Mistral 7B

Reference 11

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source=pdf_text observed=2026-08-04T06:49:06.878429Z digest=sha256:e0ee743de7e75502cb1baacaaa3985d65afbc7d40752eda7f8abeec942422cef

Observation e13d14ad-bcdf-44af-a01f-56fddd14c7c6 · outbound

This paper cites InferFix: End-to-End Program Repair with LLMs.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code InferFix: End-to-End Program Repair with LLMs

Reference 12

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source=pdf_text observed=2026-08-04T06:49:06.947279Z digest=sha256:f6e4d3ff21d06bc00fee88105abd82d52e5a6ee5d852a337d8e23b7210b5439a

Observation ebd94fba-b7fb-4ec2-808a-5d8a40eaf7d2 · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:07.070505Z digest=sha256:de4472471796607b0b6403349aaa9815f4a5426edcbc9e25de52c34197a588ee

Observation 4cdc9301-feb2-4134-ae65-74704c8e8b51 · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:07.165673Z digest=sha256:ff36a1a93cface01f12389817602ade04a48e3251ea18afc21221882851b8d2e

Observation 678cb1fb-c918-4529-ad68-d979ead4f61f · outbound

This paper cites The Impact of Prompt Programming on Function-Level Code Generation.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code The Impact of Prompt Programming on Function-Level Code Generation

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:07.249389Z digest=sha256:97b62ad0f5843a7b7fabb87f3986fc30f87be444a4988f87fec80a00fb070b51

Observation d741f7b4-8c74-445e-b41a-cd87d9e056b6 · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:07.326008Z digest=sha256:0938f898d05ab4ab50a1f0b8d78f8bbea547bc64591e27c88cfd5148a95b9c56

Observation d709ccd8-3d7a-47ea-bb2f-a3ede45533ec · outbound

This paper cites Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testing.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testing

Reference 17

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source=pdf_text observed=2026-08-04T06:49:07.386484Z digest=sha256:4c6d5f3d545e8ac666a0e0e4f9a12a318e0cfa6fe9390d8211c1df2370e6bfc4

Observation 467f1f17-883d-4cb7-a250-bffa62ab9c29 · outbound

This paper cites SOEN-101: Code Generation by Emulating Software Process Models Using Large Language Model Agents.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code SOEN-101: Code Generation by Emulating Software Process Models Using Large Language Model Agents

Reference 18

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no resolver link, observed 2026-08-04T06:49:07.442627Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:07.442627Z digest=sha256:c308c4b4b0eab475d6fd4b14a1c4fbb342a17f46ca6c73b717fd862d7570bcd9

Observation 05c266ad-988c-4165-aab7-12e4ff97d56a · outbound

This paper cites StarCoder 2 and The Stack v2: The Next Generation.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code StarCoder 2 and The Stack v2: The Next Generation

Reference 19

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no resolver link, observed 2026-08-04T06:49:07.515843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:07.515843Z digest=sha256:713fa391a3075afaa89d907cd4d01eabe63df5f1fae8da18a0dbd17b7ba6f6b6

Observation 17b75d6b-1058-4fbf-b666-2dbcd2bc0ef6 · outbound

This paper cites Precision or Peril: A PoC of Python Code Quality from Quantized Large Language Models.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Precision or Peril: A PoC of Python Code Quality from Quantized Large Language Models

Reference 20

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no resolver link, observed 2026-08-04T06:49:07.624403Z

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source=pdf_text observed=2026-08-04T06:49:07.624403Z digest=sha256:ffdb356a583a2970689215b7f4966bf81a54f0f40da4a89be21fc780f474bfce

Observation 93deb7bd-19d7-4a82-afe3-205f91a489a1 · outbound

This paper cites Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 21

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no resolver link, observed 2026-08-04T06:49:07.787886Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T06:49:07.787886Z digest=sha256:aa944c23215e29f32519fb4f46768e694d061419ea2e2207d60af99b32bc95a7

Observation 02da1c6a-f6b6-4ec5-9ef6-70edad89e2c1 · outbound

This paper cites Evaluating the Effectiveness of LLMs in Fixing Maintainability Issues in Real-World Projects.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Evaluating the Effectiveness of LLMs in Fixing Maintainability Issues in Real-World Projects

Reference 22

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no resolver link, observed 2026-08-04T06:49:07.865706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:07.865706Z digest=sha256:c5180844069c41acbd6173b1270ade869619bf7be2956ef55fdb899df14bc477

Observation bab71050-9250-410e-955c-8194910a99c9 · outbound

This paper cites On the Diffusion of Test Smells in LLM-Generated Unit Tests.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code On the Diffusion of Test Smells in LLM-Generated Unit Tests

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:08.029259Z digest=sha256:37a59a929dde9c8f0a9268eb9bb68afea68342765e55396805c3206c071a2e58

Observation c175bb4f-2c0d-4b26-be0d-b59c3c25b458 · outbound

This paper cites Palacio, Daniel Rodriguez-Cardenas, Alejandro Velasco, Dipin Khati, Kevin Moran, and Denys Poshyvanyk.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Palacio, Daniel Rodriguez-Cardenas, Alejandro Velasco, Dipin Khati, Kevin Moran, and Denys Poshyvanyk

Reference 24

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source=pdf_text observed=2026-08-04T06:49:08.111414Z digest=sha256:9916d0f015999321b3d7a521aff5d9341d6addd11bb2a9e1dc3a9cf8db646c48

Observation 20dac522-2035-49e8-8211-22363ee140ad · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 25

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:08.163894Z digest=sha256:3c09d9db65c5761c6c44b3325220b4c8cf61d4fd96d4fd8c9f4b940fc176a324

Observation 3ff0be6f-3915-4c01-9f90-26279f77ca99 · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 26

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:08.252378Z digest=sha256:2ec68487388d65d2bbf5fca02e44e68efb2c74c171e9729a975b6f4432b8af0c

Observation eb9f34ff-0d43-4973-b05f-9c1fab3b12c4 · outbound

This paper cites Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributions.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributions

Reference 27

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source=pdf_text observed=2026-08-04T06:49:08.330142Z digest=sha256:d2db2f2253c9d4f871e5927c254dc046dee0a7bd5af8f251914c37fe0e3f66e8

Observation c1a02a9d-df7d-4151-988d-022d44db193c · outbound

This paper cites 2018.The Book of Why: The New Science of Cause and Effect(1st ed.).

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code 2018.The Book of Why: The New Science of Cause and Effect(1st ed.)

Reference 28

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source=pdf_text observed=2026-08-04T06:49:08.395020Z digest=sha256:acc55fcf159e9c6ab6dceb77b4c6938f7fc9788f0d1cf937b07b06595ebd5e15

Observation 8135f9e5-7d4c-4a6c-b4d0-c6201f215f01 · outbound

This paper cites Qwen2.5 Technical Report.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Qwen2.5 Technical Report

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:08.436609Z digest=sha256:5e676ece4eefca42513c4c6a38eca8d29425facd54d47bcb30bae51a00191f03

Observation 10e7115c-291b-4f89-94d0-440766cd94f9 · outbound

This paper cites Sánchez-García, and Juan Car- los Pérez-Arriaga.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Sánchez-García, and Juan Car- los Pérez-Arriaga

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:08.567486Z digest=sha256:0a38e1d6f8297ab215168df4981bea18612e8a7d03daf1f47de7360d16428855

Observation 62cff749-8486-46c0-ae29-2ae84fa6d2fe · outbound

This paper cites CodeBLEU: a Method for Automatic Evaluation of Code Synthesis.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code CodeBLEU: a Method for Automatic Evaluation of Code Synthesis

Reference 31

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no resolver link, observed 2026-08-04T06:49:08.638543Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:08.638543Z digest=sha256:40589b2c184ebe55b54f8ccf8a12ad932ec299ac4d1fbd5a3da101f255d2b4ab

Observation 78594478-5816-4221-ba1b-8356c8171e5a · outbound

This paper cites Benchmarking Causal Study to Interpret Large Language Models for Source Code.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Benchmarking Causal Study to Interpret Large Language Models for Source Code

Reference 32

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source=pdf_text observed=2026-08-04T06:49:08.796729Z digest=sha256:d8adcad9b98f22b15f508cd8fdca8c15a832eab5c6ac265502001c16120f2a28

Observation c82abffe-873f-4a3f-b3a4-1f66eb628ae5 · outbound

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

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Code Llama: Open Foundation Models for Code

Reference 33

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:08.893302Z digest=sha256:e43312bb45040613a3cc636bb2198c1d9e9859d82774e59a6eb4b69cdea7ea27

Observation d948be2a-1ca2-462e-9238-161444dc2836 · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 34

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no resolver link, observed 2026-08-04T06:49:09.043329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:09.043329Z digest=sha256:914a150bff83c172ef4072892b07c1f5caa6a1c39a84eaac8a69a1e1ee7a3f5d

Observation 3d2f969d-7966-4788-ba46-415dc18407ee · outbound

This paper cites DoWhy: An End-to-End Library for Causal Inference.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code DoWhy: An End-to-End Library for Causal Inference

Reference 35

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:49:09.194955Z digest=sha256:73a59df2fc0f71ed239684ae9640b699a5835f4bbe19f1e6dc489a4100cc2857

Observation 1630e8c7-8403-4335-be65-17f75d70c874 · outbound

This paper cites Majumder, Maisha R.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Majumder, Maisha R

Reference 36

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source=pdf_text observed=2026-08-04T06:49:09.359797Z digest=sha256:a2f1c084df9f39abfac38d01654a435d8c8db5c1ee336ff3c1dcfc8060bb87ae

Observation ba12847e-d0fb-47a4-8d2c-13e2e6fa69c6 · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 37

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source=pdf_text observed=2026-08-04T06:49:09.590514Z digest=sha256:500daeab093b93e81adba77ebc79235960d545d4ef0840cb71cafe215cf6e65b

Observation 5e4bdbb0-0806-41a7-b3dd-794e381522e9 · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 38

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Observation e5fc96cb-55ff-4786-8074-c90b5cae854f · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 39

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Observation 8fd8663d-bb06-4b74-94d8-5bff821b0586 · outbound

This paper cites Code Readability in the Age of Large Language Models: An Industrial Case Study from Atlassian.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Code Readability in the Age of Large Language Models: An Industrial Case Study from Atlassian

Reference 40

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Observation 579c94d2-d8d7-43b9-9cc9-0c983d0cb6e8 · outbound

This paper cites Bugs in Large Language Models Generated Code: An Empirical Study.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Bugs in Large Language Models Generated Code: An Empirical Study

Reference 41

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Observation eb8e03aa-b46d-4e9e-97fa-01986a6c069e · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 42

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Observation 75937992-3c33-4279-abbe-2724dc63252a · outbound

This paper cites How Propense Are Large Language Models at Producing Code Smells? A Benchmarking Study.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code How Propense Are Large Language Models at Producing Code Smells? A Benchmarking Study

Reference 43

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Observation 1464a0db-61f8-4841-8267-7b503aaad29e · outbound

This paper cites A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research

Reference 44

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Observation 66268154-c638-40f0-a6c8-f34844030598 · outbound

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A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 45

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Observation f276b83f-c082-417e-acfb-9633bf09bfd8 · outbound

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A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 46

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A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 47

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Observation b3730327-edd3-4568-b663-afb970f6c6e6 · outbound

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A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 48

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Observation de94bb6e-a4bd-4521-a930-35928cfeb8fa · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 49

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Observation 88c14944-9a3f-4d3b-9ce6-2b119b05a107 · outbound

This paper cites an unresolved cited work.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Unresolved cited work

Reference 50

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Observation dac42bef-5b25-4d36-b2f1-8906c18b8a89 · outbound

This paper cites Beyond Correctness: Benchmarking Multi-dimensional Code Generation for Large Language Models.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Beyond Correctness: Benchmarking Multi-dimensional Code Generation for Large Language Models

Reference 51

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Observation aa3022c3-7412-4315-9e0d-156ad4680472 · outbound

This paper cites InProceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering (Singapore, Singapore)(ASE ’16).

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code InProceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering (Singapore, Singapore)(ASE ’16)

Reference 2016

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Observation ecf0bded-1ae8-49f9-8493-8a9c62a81490 · outbound

This paper cites 2023), 111741.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code 2023), 111741

Reference 2023

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

This paper cites Studying How Configurations Impact Code Generation in LLMs: the Case of ChatGPT.

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

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Pith citing papers

Observation 53c7b57f-8bbd-4ceb-a2c5-c2bc145ef570 · inbound

SmellBench: Evaluating LLM Agents on Architectural Code Smell Repair cites this paper.

SmellBench: Evaluating LLM Agents on Architectural Code Smell Repair A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code

Reference 24

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arxiv_id, observed 2026-08-04T02:39:45.615352Z

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Observation 6ea58c48-5844-41b8-a140-23242dfa55fd · inbound

SmellBench: Evaluating LLM Agents on Architectural Code Smell Repair cites this paper.

SmellBench: Evaluating LLM Agents on Architectural Code Smell Repair A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code

Reference 24

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arxiv_id, observed 2026-08-04T02:39:45.615352Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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