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Paper Citation Record · LEDGER

Towards an Understanding of Large Language Models in Software Engineering Tasks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2308.11396.

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

pith.paper-citation-record.v1
2308.11396 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:44:51.715251Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T03:58:51.419271Z

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 f06601e7-6ebb-4b9a-a879-216c6ff1b62c · inbound

SWE-bench: Can Language Models Resolve Real-World GitHub Issues? cites this paper.

SWE-bench: Can Language Models Resolve Real-World GitHub Issues? Towards an Understanding of Large Language Models in Software Engineering Tasks

Reference 145

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T14:02:01.274249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T14:02:01.201111Z digest=sha256:e3f0002502252976da1f83f863f8f204f7cb353d5144337a8230aa50bbb6881b

Observation fd0b371c-f90d-4996-bdb3-a2ad72b8a069 · inbound

CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology cites this paper.

CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology Towards an Understanding of Large Language Models in Software Engineering Tasks

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-05-24T03:58:51.422402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-24T03:58:32.556725Z digest=sha256:826c9f1b7a61332f9c6bfd90fc648670f5087319fcdab92b2151325e5d32ddd2

Observation 9bd672ba-b2cd-46d9-bb69-b3e9d2d6b03e · inbound

Are Decoder-Only Large Language Models the Silver Bullet for Code Search? cites this paper.

Are Decoder-Only Large Language Models the Silver Bullet for Code Search? Towards an Understanding of Large Language Models in Software Engineering Tasks

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-23T18:43:19.168296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T18:39:21.915976Z digest=sha256:2f6a2a75c0e53d345fd6e5556e8bb5d39d0a662bd2834e267d03ee52f0aee90a

Observation d5ecd1a3-b52e-42c6-abfb-4daa79345337 · inbound

Accelerating Automatic Program Repair with Dual Retrieval-Augmented Fine-Tuning and Patch Generation on Large Language Models cites this paper.

Accelerating Automatic Program Repair with Dual Retrieval-Augmented Fine-Tuning and Patch Generation on Large Language Models Towards an Understanding of Large Language Models in Software Engineering Tasks

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-06T17:44:51.715251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:44:51.715251Z digest=sha256:94f85a0fbad92e369d29b007c8423a6217c7b89545c23716d5e2f434d728687a

Observation 60071b77-a760-4c29-abd8-e8b7ee75eb1c · inbound

Story Point Estimation Using Large Language Models cites this paper.

Story Point Estimation Using Large Language Models Towards an Understanding of Large Language Models in Software Engineering Tasks

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T15:30:07.557102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T15:27:47.957035Z digest=sha256:4f5863348c5ed11caa360bdbe821b2a978c10b19d6c2bcaead0846743a9adb96