Paper Citation Record · LEDGER

An Empirical Study on the Code Refactoring Capability of Large Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2411.02320.

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

pith.paper-citation-record.v1
2411.02320 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 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 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:44:15.420898Z

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

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation eb9883fe-ecf4-4de7-a348-109af9d5f89d · inbound

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards cites this paper.

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:46:37.300554Z

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 e9901042-3f7e-450f-a88d-adac0756ea11 · inbound

Taxonomy of migration scenarios for Qiskit refactoring using LLMs cites this paper.

Taxonomy of migration scenarios for Qiskit refactoring using LLMs An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:44:15.420898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 439e8265-1dc0-4352-8220-e8b6908b13c6 · inbound

MCTS-Refined CoT: High-Quality Fine-Tuning Data for LLM-Based Repository Issue Resolution cites this paper.

MCTS-Refined CoT: High-Quality Fine-Tuning Data for LLM-Based Repository Issue Resolution An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T00:49:32.723197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37d51472-bd03-4e2d-93ef-76f54e6bc0bf · inbound

Automatic Qiskit Code Refactoring Using Large Language Models cites this paper.

Automatic Qiskit Code Refactoring Using Large Language Models An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:49.181710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40ace3df-02c6-4ef0-bc86-9400237303f6 · inbound

Your Build Scripts Stink: The State of Code Smells in Build Scripts cites this paper.

Your Build Scripts Stink: The State of Code Smells in Build Scripts An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-19T08:37:11.776749Z

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 91233b36-a80b-42d4-95f5-b740e19a4d6f · inbound

Can LLMs Replace Humans During Code Chunking? cites this paper.

Can LLMs Replace Humans During Code Chunking? An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T23:10:14.412425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59ef931f-3e2a-4d93-80df-e9e74bbff9e4 · inbound

ROSE: Transformer-Based Refactoring Recommendation for Architectural Smells cites this paper.

ROSE: Transformer-Based Refactoring Recommendation for Architectural Smells An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T16:47:55.180636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b1a0e5d-836a-4a4e-b781-20afb28b237f · inbound

Structural Anchors and Reasoning Fragility:Understanding CoT Robustness in LLM4Code cites this paper.

Structural Anchors and Reasoning Fragility:Understanding CoT Robustness in LLM4Code An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:46:06.100975Z

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 7004cba9-676a-4499-8bd5-d34be7245682 · inbound

Foundation Models as Oracles for Refactoring Correctness Detection cites this paper.

Foundation Models as Oracles for Refactoring Correctness Detection An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:00:36.086332Z

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 767465cb-1c5a-41e5-a329-70189015d717 · inbound

Foundation Models as Oracles for Refactoring Correctness Detection cites this paper.

Foundation Models as Oracles for Refactoring Correctness Detection An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-07-04T01:49:21.465941Z

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 02b790aa-bed1-44b0-af24-f9ea8ab1fcba · inbound

AI-Generated Smells: An Analysis of Code and Architecture in LLM and Agent-Driven Development cites this paper.

AI-Generated Smells: An Analysis of Code and Architecture in LLM and Agent-Driven Development An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:50:39.868238Z

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 4feac4a4-c035-4227-8f62-b6d545b87215 · inbound

Patterns of Developer Adoption of LLM-Generated Code Refactoring Suggestions cites this paper.

Patterns of Developer Adoption of LLM-Generated Code Refactoring Suggestions An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:21:08.450811Z

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 8a370c29-d2af-46d6-8366-a13502395acb · inbound

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

SmellBench: Evaluating LLM Agents on Architectural Code Smell Repair An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T01:05:49.930971Z

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 5e9715c4-876e-4a10-ae3f-b5c11fd73ec6 · inbound

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

SmellBench: Evaluating LLM Agents on Architectural Code Smell Repair An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:02:21.881431Z

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 b5eb3b99-c3a5-42f0-a3b0-9cce3bfc8eb0 · inbound

Qiskit Code Migration with LLMs cites this paper.

Qiskit Code Migration with LLMs An Empirical Study on the Code Refactoring Capability of Large Language Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-06-26T16:29:35.432346Z

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.