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Paper Citation Record · LEDGER

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation

As of 11 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2502.00611.

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

pith.paper-citation-record.v1
2502.00611 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:22:08.048997Z

measured 16 of 16 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy14
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eb82b189-6de7-4583-a707-d7e85d6d07a4 · outbound

This paper cites Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-09T18:22:07.975846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:22:07.975846Z digest=sha256:15c289851c3623f539bc52e0b8461d79dfb338d01908527673c65e46061685c7

Observation cb240624-9091-4c54-b42b-d8f05f6ca517 · outbound

This paper cites Artificial intelligence faces reproducibility crisis.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation Artificial intelligence faces reproducibility crisis

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.418708Z

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=2026-08-09T18:22:07.981866Z digest=sha256:a95dd03ac39ac6ca40343383dfa4e4ca89d3f5fe0b571ae5f7e20d9766e917bc

Observation de4c11ac-5dd6-413b-a8ba-eeeb47d19e5e · outbound

This paper cites and Larochelle, H., 2021.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation and Larochelle, H., 2021

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.403386Z

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=2026-08-09T18:22:07.986839Z digest=sha256:7155108601e7d63df4fd884805ddada04e7643d691558be216b81e98953e2701

Observation dec96cb2-a304-4826-bed2-19160b1e8a9c · outbound

This paper cites and Kjensmo, S., 2018, April.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation and Kjensmo, S., 2018, April

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.388701Z

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=2026-08-09T18:22:07.991721Z digest=sha256:c558e2b9c105b56f4523269806992d3dbf2d581f141ada792a4365e6f6ec5d45

Observation f0323530-1266-46c5-a05b-6b4d00b65e14 · outbound

This paper cites and Dane, S., 2018.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation and Dane, S., 2018

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.373494Z

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=2026-08-09T18:22:07.996744Z digest=sha256:0e46d5373dd6ea9f2c176108e854268e7e7a94a0761e31059073d6163c6efc73

Observation 3fb3b970-90f3-415c-a767-16a1e30876af · outbound

This paper cites The Foundations of Verification: Code Verifi- cation.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation The Foundations of Verification: Code Verifi- cation

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.357993Z

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=2026-08-09T18:22:08.002044Z digest=sha256:e39ed4d061860b07d94395bcb51ba9eebca5266b9997338dd776f1da83a673b9

Observation 2fffde67-a8ff-4d48-bc57-af39879153c1 · outbound

This paper cites A step toward quantifying independently reproducible machine learning research.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation A step toward quantifying independently reproducible machine learning research

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.342719Z

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=2026-08-09T18:22:08.007381Z digest=sha256:439a1b4a066195b241119d77f88f431ac15d57492ea16e935e8be9ae14db90f7

Observation c03b974b-87e4-4bac-9d2e-6607a2d03a17 · outbound

This paper cites and Zuo, C., 2023.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation and Zuo, C., 2023

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.327044Z

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=2026-08-09T18:22:08.012063Z digest=sha256:c584a6a576c5403c3e65a5b7f33ae67c6155bb1e4ec5e66bfe43c4fb80740235

Observation 48a5c593-bafc-4f0e-afcc-ce2bfdc6402b · outbound

This paper cites and Riedel, S.,.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation and Riedel, S.,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.311678Z

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=2026-08-09T18:22:08.016754Z digest=sha256:47e97c0b26b4bcf5d9cf0ee2b6dde6537f63ed94ba4244f07de180b88ffb955a

Observation 668cc879-4ab0-4efe-b112-25f94823db81 · outbound

This paper cites LlamaIndex.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation LlamaIndex

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.279058Z

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=2026-08-09T18:22:08.026127Z digest=sha256:dfc5353c236e86eab5c9f0aa3cf1da57ad3ae330b62c77c7e8707d999691fe7a

Observation ee38fee6-5824-4268-a165-c63c70dcbf07 · outbound

This paper cites NVIDIA NeMo.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation NVIDIA NeMo

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.263625Z

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=2026-08-09T18:22:08.030747Z digest=sha256:06bba251644ad1662572333a2b43139349c3abe4bd0eabb59b24493ff5d350b8

Observation aa45e365-ce3b-437e-84f1-5d35d6664d6d · outbound

This paper cites Introducing Meta Llama 3: The most capable openly avail- able LLM to date.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation Introducing Meta Llama 3: The most capable openly avail- able LLM to date

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.148312Z

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=2026-08-09T18:22:08.035355Z digest=sha256:77933a505904e68a1ad3262ce026632939d19bc3d5497ede02e826e2976bd07b

Observation b74179bb-0c8c-42fc-9f86-9a86e4ce5f31 · outbound

This paper cites NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-09T18:22:08.039790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:22:08.039790Z digest=sha256:5495174f6911b5546371d7b793b6f49a4b182f15474dba9fd9642b509f48da4c

Observation f301ee5b-2ea3-482a-a847-acac5b734c33 · outbound

This paper cites NVIDIA Retrieval QA Mistral 4B Reranking v3.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation NVIDIA Retrieval QA Mistral 4B Reranking v3

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.134001Z

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=2026-08-09T18:22:08.044594Z digest=sha256:850d8f77be98be88a793fb2ed08f3f38326126067708d480d97b6544baa891e7

Observation ac984c04-f3cc-4fb4-a13b-8b9c190462ca · outbound

This paper cites and Toutanova, K., 2019, June.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation and Toutanova, K., 2019, June

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.117292Z

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=2026-08-09T18:22:08.048997Z digest=sha256:d246aba41687424f11c67012dc6f48814e2bbe987b0efaedfcefdf9dbb264f52

Observation 59474ca0-ea30-40b5-bd84-51b9df20c135 · outbound

This paper cites Advances in Neural Information Processing Systems.

Enhancing Code Consistency in AI Research with Large Language Models and Retrieval-Augmented Generation Advances in Neural Information Processing Systems

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T18:22:08.295790Z

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=2026-08-09T18:22:08.021575Z digest=sha256:96d9087e34b20c37b6a5c3df482065d0c1344db86f54395bc70e0fc8403912f1

Pith citing papers

No inbound Pith citation observations are available.