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Paper Citation Record · LEDGER

A Systematic Literature Review of Explainable AI for Software Engineering

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.06065.

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

pith.paper-citation-record.v1
2302.06065 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T07:05:03.545756Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T17:46:41.902400Z

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 d2098201-0f82-48be-bc12-b61697caad38 · inbound

Minimal Data, Maximum Clarity: A Heuristic for Explaining Optimization cites this paper.

Minimal Data, Maximum Clarity: A Heuristic for Explaining Optimization A Systematic Literature Review of Explainable AI for Software Engineering

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-18T17:46:41.906112Z

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=2026-05-18T17:46:23.625663Z digest=sha256:454d694a2abfa7c17cab00cc0e8b4715813107024132f57bc2ed7f8f8ed1a581

Observation 75bad484-957b-407a-ad47-549c341a2c19 · inbound

A Preliminary Study on Explaining Risk of Code Changes using LLM-Based Prediction Models cites this paper.

A Preliminary Study on Explaining Risk of Code Changes using LLM-Based Prediction Models A Systematic Literature Review of Explainable AI for Software Engineering

Reference 16

Resolution
unresolved
no resolver link, observed 2026-07-12T07:05:03.545756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T07:05:03.545756Z digest=sha256:97dea0b1ee53c0313a9012c329f5b53107ddb8482362742b8725a197a4368142