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Paper Citation Record · LEDGER

Evaluating the Correctness of Explainable AI Algorithms for Classification

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2105.09740.

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

pith.paper-citation-record.v1
2105.09740 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:54:19.353207Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T20:23:24.646865Z

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 26712ece-70e8-4225-b319-3af78a7bf8a7 · inbound

Explainable AI needs formalization cites this paper.

Explainable AI needs formalization Evaluating the Correctness of Explainable AI Algorithms for Classification

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-23T20:23:24.650370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-23T20:21:52.229228Z digest=sha256:52e506271860136c6147b9c50415a3388e1ab8d443eb7888a9df172dceb64d5a

Observation 185d5437-3e7e-46e6-a41d-4f77a0c82b82 · inbound

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation cites this paper.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Evaluating the Correctness of Explainable AI Algorithms for Classification

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-11T13:54:19.353207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:54:19.353207Z digest=sha256:a0ceed083e79a0ef2cda5d09056cc37fa91729830f1cd3e0e5a0857703fe1355

Observation 63b8a5e9-c535-44c8-a549-6297fcf55f86 · inbound

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions cites this paper.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Evaluating the Correctness of Explainable AI Algorithms for Classification

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T15:27:09.352549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:27:09.352549Z digest=sha256:8a20a2a827bcc1d5646e1cff653f33cf56c89dc3269c79ac310a537894e5c454