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Paper Citation Record · LEDGER

Rethinking Stability for Attribution-based Explanations

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2203.06877.

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

pith.paper-citation-record.v1
2203.06877 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:46:34.740816Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T19:01:17.874068Z

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 bea20a21-6f76-4f56-83fb-0625c5acd44e · inbound

VARSHAP: Addressing Global Dependency Problems in Explainable AI with Variance-Based Local Feature Attribution cites this paper.

VARSHAP: Addressing Global Dependency Problems in Explainable AI with Variance-Based Local Feature Attribution Rethinking Stability for Attribution-based Explanations

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T05:46:34.740816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:46:34.740816Z digest=sha256:cecc2317cae97d793c988ba1a75bb89938074676ba9d99a5ada3374b819e601c

Observation f399a31c-93a1-48ef-a6e1-f22498ed63c1 · inbound

Assessing the Noise Robustness of Class Activation Maps: A Framework for Reliable Model Interpretability cites this paper.

Assessing the Noise Robustness of Class Activation Maps: A Framework for Reliable Model Interpretability Rethinking Stability for Attribution-based Explanations

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T16:39:26.223640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T16:39:26.223640Z digest=sha256:63065e139e5b59e95d5d2e8797d1f28dfd81f3f4dc78e58b0b08756c98dc6950

Observation 5b52153e-3850-405e-994a-cb58665e14cf · inbound

Value bounds and Convergence Analysis for Averages of LRP attributions cites this paper.

Value bounds and Convergence Analysis for Averages of LRP attributions Rethinking Stability for Attribution-based Explanations

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-04T20:01:05.448889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:01:05.448889Z digest=sha256:b1fa75f50cbafcf4e085fe6d53dbec2cf49b8788fd7f4429db1e9f476d921324

Observation 44cea3a8-a85a-4f52-a19a-f6858c900bc2 · inbound

Foundation models for discovering robust biomarkers of neurological disorders from dynamic functional connectivity cites this paper.

Foundation models for discovering robust biomarkers of neurological disorders from dynamic functional connectivity Rethinking Stability for Attribution-based Explanations

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:01:17.877082Z

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=2026-05-08T12:55:43.452286Z digest=sha256:67c3731812be4fa7e57c4202040ac544b18e829d40bfc9c142300f21c1d66647