Paper Citation Record · LEDGER

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models

As of 17 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2501.09745.

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

pith.paper-citation-record.v1
2501.09745 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:44:06.490378Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:09:41.792404Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:09:44.721635Z

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy22
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6cc72a6d-c13b-41e3-8bcf-7dd845c30d2a · outbound

This paper cites Change distilling:tree differencing for fine-grained source code change extraction,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Change distilling:tree differencing for fine-grained source code change extraction,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:07.223411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 75bf407e-e793-4c63-ac75-4433fa1a7c43 · outbound

This paper cites Juice: A large scale distantly supervised dataset for open domain context-based code generation,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Juice: A large scale distantly supervised dataset for open domain context-based code generation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:07.204776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8ac32a24-5b24-4644-923f-310ecd3a02ee · outbound

This paper cites Teaching Large Language Models to Self-Debug.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Teaching Large Language Models to Self-Debug

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T19:44:06.296150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a0bc98c-b94a-4471-9ab9-0e19eb7931cd · outbound

This paper cites Flashattention-2: Faster attention with better parallelism and work partitioning,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Flashattention-2: Faster attention with better parallelism and work partitioning,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:07.183115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e987b04e-94e4-4556-a31e-2195ca1dd5e6 · outbound

This paper cites Pyevolve: Automating frequent code changes in python ml systems,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Pyevolve: Automating frequent code changes in python ml systems,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:07.162111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 73dc75a7-0bd1-437b-8352-4ea340693c05 · outbound

This paper cites Refactoring operations grounded in manual code changes,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Refactoring operations grounded in manual code changes,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:07.143211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d5a50894-1dcc-4169-9682-3c112785101a · outbound

This paper cites Distilkaggle: A distilled dataset of kaggle jupyter notebooks,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Distilkaggle: A distilled dataset of kaggle jupyter notebooks,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:07.121959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8f57e56a-7b14-4103-96c0-eab85abc8f9f · outbound

This paper cites Rest api endpoints for repositories,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Rest api endpoints for repositories,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:07.101137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b76116f5-dbda-4542-92e3-9c33e7f13d90 · outbound

This paper cites Deepseek-coder: When the large language model meets programming – the rise of code intelligence,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Deepseek-coder: When the large language model meets programming – the rise of code intelligence,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:07.080975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f29b1b28-6977-4a29-a713-0d4185e6798c · outbound

This paper cites LoRA: Low-rank adaptation of large language models,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models LoRA: Low-rank adaptation of large language models,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T19:44:06.338814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2879bb3b-81f6-421f-811a-4d5130aa87a5 · outbound

This paper cites Jupyter notebooks - a publishing format for reproducible computational workflows,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Jupyter notebooks - a publishing format for reproducible computational workflows,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:07.043947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0c4f1ca3-3e1e-4498-a3b0-0408cb4b253d · outbound

This paper cites Automating code review activities by large-scale pre-training,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Automating code review activities by large-scale pre-training,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:07.022879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cf2f4372-2e35-47a8-b32c-efae582c934d · outbound

This paper cites Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:06.982809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b275e015-57f1-4cdf-b3b8-d171072ba915 · outbound

This paper cites Orange: a method for evaluating automatic evaluation metrics for machine translation,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Orange: a method for evaluating automatic evaluation metrics for machine translation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:06.958842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3b39994b-cfd2-4dce-b1c4-ce2c66dc8a61 · outbound

This paper cites PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T19:44:06.372395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da941b72-23e1-44e7-aea2-429808149336 · outbound

This paper cites Search microsoft copilot: Your everyday ai companion.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Search microsoft copilot: Your everyday ai companion

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T19:44:06.380365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 861d631b-8f7c-449a-ae57-b1d878f05e30 · outbound

This paper cites Learning deep semantics for test completion,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Learning deep semantics for test completion,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:06.916413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5df464d0-39e0-4fea-b327-6ab26e8e1e48 · outbound

This paper cites GPT-4 Technical Report.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models GPT-4 Technical Report

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T19:44:06.392210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a55e9c33-d65b-47ef-b713-377ff771b89d · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Bleu: a method for automatic evaluation of machine translation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:06.895502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 12c519ff-a1b7-4772-9ecb-2b0a25646730 · outbound

This paper cites Kgtorrent: A dataset of python jupyter notebooks from kaggle,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Kgtorrent: A dataset of python jupyter notebooks from kaggle,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:06.870336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a3239502-6485-4315-9a91-03db93c7d679 · outbound

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

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models CodeBLEU: a Method for Automatic Evaluation of Code Synthesis

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T19:44:06.414663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac9b5004-3fba-47a0-9474-df51316ece98 · outbound

This paper cites The programmer’s assistant: Conversational interaction with a large language model for software development,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models The programmer’s assistant: Conversational interaction with a large language model for software development,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:06.843919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 480c6701-deb7-42c9-b3c1-f6de3d6a1f5b · outbound

This paper cites Code llama: Open foundation models for code,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Code llama: Open foundation models for code,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T19:44:06.442852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77d7f9de-df80-4dc6-a3d3-b0b094e903b5 · outbound

This paper cites Intellicode compose: code generation using transformer,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Intellicode compose: code generation using transformer,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:06.806008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 726d709c-8446-4b2b-95c8-70c05e932124 · outbound

This paper cites Documentation matters: Human- centered ai system to assist data science code documentation in computa- tional notebooks,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Documentation matters: Human- centered ai system to assist data science code documentation in computa- tional notebooks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:06.785340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 78272934-34d6-4c11-a8f7-6e4ab9cb1449 · outbound

This paper cites ClinicalGPT: Large Language Models Finetuned with Diverse Medical Data and Comprehensive Evaluation.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models ClinicalGPT: Large Language Models Finetuned with Diverse Medical Data and Comprehensive Evaluation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T19:44:06.461047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f19f0dc5-0aac-4f99-9c60-331c3d5539fc · outbound

This paper cites On-Device LLMs for SMEs: Challenges and Opportunities.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models On-Device LLMs for SMEs: Challenges and Opportunities

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T19:44:06.467762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e54c908c-078c-4243-b781-91dd130eb304 · outbound

This paper cites Natural language to code generation in interactive data science notebooks,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Natural language to code generation in interactive data science notebooks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:06.753397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8a34b7cd-38ec-4230-bab9-ee347fe384cc · outbound

This paper cites Multilingual code co- evolution using large language models,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Multilingual code co- evolution using large language models,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:06.722603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c6729783-67ca-4977-9cfb-be916fc89725 · outbound

This paper cites Large language model in sd-wan intelligent operations and maintenance,.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models Large language model in sd-wan intelligent operations and maintenance,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:06.703204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ce26bff2-9be3-433a-9020-ea7330dda47a · outbound

This paper cites 1035–1047.

Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models 1035–1047

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:44:07.002321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation 5b6bb04f-aaea-4af3-82cb-3e744434d529 · inbound

CRABS: A syntactic-semantic pincer strategy for bounding LLM interpretation of Python notebooks cites this paper.

CRABS: A syntactic-semantic pincer strategy for bounding LLM interpretation of Python notebooks Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:09:44.767819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.