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Paper Citation Record · LEDGER

Exploring the Capabilities of LLMs for Code Change Related Tasks

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2407.02824.

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

pith.paper-citation-record.v1
2407.02824 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:59:48.244122Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:35:42.447050Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 7014ef38-c317-4cf7-80c2-c416dd5b6dcb · inbound

Code Change Intention, Development Artifact and History Vulnerability: Putting Them Together for Vulnerability Fix Detection by LLM cites this paper.

Code Change Intention, Development Artifact and History Vulnerability: Putting Them Together for Vulnerability Fix Detection by LLM Exploring the Capabilities of LLMs for Code Change Related Tasks

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T14:48:57.471669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:48:57.471669Z digest=sha256:36eb162c50ccd5a93fd0de7e26ac41c9b519c429c7be5a7f8099f92e0102539b

Observation 2a6b757f-817e-4b4c-8008-795e29b11e53 · inbound

BitsAI-CR: Automated Code Review via LLM in Practice cites this paper.

BitsAI-CR: Automated Code Review via LLM in Practice Exploring the Capabilities of LLMs for Code Change Related Tasks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T14:40:07.106321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:40:07.106321Z digest=sha256:23b3b0c72ae0f221c1dfda7f7c3e663dbbfb6c01edc5d5cbccc1e057aa18d4e1

Observation fe8ab605-c934-4a1e-9ced-543cfeb035f8 · inbound

Resource-Efficient & Effective Code Summarization cites this paper.

Resource-Efficient & Effective Code Summarization Exploring the Capabilities of LLMs for Code Change Related Tasks

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-09T04:23:34.835072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:23:34.835072Z digest=sha256:1ba58d7d33cd36bb79ce0615092e0203d3799a0815a8deeaa27f05a6db71239d

Observation b2bdd644-dfc6-4a54-974c-ded7904b1df6 · inbound

Intention is All You Need: Refining Your Code from Your Intention cites this paper.

Intention is All You Need: Refining Your Code from Your Intention Exploring the Capabilities of LLMs for Code Change Related Tasks

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-08T10:14:03.433023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:14:03.433023Z digest=sha256:f1f364ac26e69914faa0fd6d454d0d8dff9e6a2a0d0cd7623cdb0428921fc7dd

Observation 78712847-8575-4c47-8702-7e9cc04fd008 · inbound

PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models cites this paper.

PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models Exploring the Capabilities of LLMs for Code Change Related Tasks

Reference 164

Resolution
unresolved
no resolver link, observed 2026-08-16T11:59:48.244122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:59:48.244122Z digest=sha256:461993e1393e45f0e5eedd4b27e0ecaea0446dd246da152409e5ab52fdd752ea

Observation b5c811ac-247e-433b-9e17-18cab15bb9b0 · inbound

Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvements cites this paper.

Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvements Exploring the Capabilities of LLMs for Code Change Related Tasks

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:35:42.452944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T04:35:42.239182Z digest=sha256:2af0ea2f21b9a98564487cbe53799b1cfe65866292ce6f8ef46d5810f2ca1c35