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Paper Citation Record · LEDGER

Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2005.06676.

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

pith.paper-citation-record.v1
2005.06676 v1

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 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:14:08.019714Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:05:27.948203Z

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 edb0dff1-df56-45ad-b95a-202ed420549f · inbound

Fair Document Valuation in LLM Summaries via Shapley Values cites this paper.

Fair Document Valuation in LLM Summaries via Shapley Values Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T13:14:08.019714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:14:08.019714Z digest=sha256:6bfa457c47d2566653027edaf1d34419c32a3c38143c61ebcd73349675b8072b

Observation 1ce0b228-6615-47dc-98a8-b87f0287eb85 · inbound

A Comparative Analysis of Influence Signals for Data Debugging cites this paper.

A Comparative Analysis of Influence Signals for Data Debugging Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions

Reference 1974

Resolution
unresolved
no resolver link, observed 2026-08-07T04:08:26.651058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:26.651058Z digest=sha256:6e92bf22b8701041d2ce55942874e6398df7628ab4ca99ee2de7131b9d734ac8

Observation 4577a052-ab1f-4dc8-a192-a4e13b33e542 · inbound

Attributing Data for Sharpness-Aware Minimization cites this paper.

Attributing Data for Sharpness-Aware Minimization Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T20:02:07.027256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:02:07.027256Z digest=sha256:d04aa9f02d3f574eb51435462ef5e2d38a5265f62612cf82e6117c70cbd9f196

Observation 7c19b59b-329b-43de-9e67-2e97852f6bfc · inbound

Newfluence: Boosting Model interpretability and Understanding in High Dimensions cites this paper.

Newfluence: Boosting Model interpretability and Understanding in High Dimensions Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:05:28.022448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T17:05:25.752311Z digest=sha256:87575e1bcb8d8d3c3e9672194d866331484ce0536c5114bb456a64e5c6b2e1ae

Observation 9d11e0b3-dfdd-4629-870c-3845dcaaf24d · inbound

destroR: A Benchmark and Adversarial-Training Defense for Bangla Transfer Models under Meaning-Preserving Attacks cites this paper.

destroR: A Benchmark and Adversarial-Training Defense for Bangla Transfer Models under Meaning-Preserving Attacks Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-03T22:30:14.797963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:30:14.797963Z digest=sha256:37897a6f41b65b019b5cd629eb1fc3d7cfd50cf8ba5f329ab0065f60e9863d3a