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Paper Citation Record · LEDGER

A Survey on Understanding, Visualizations, and Explanation of Deep Neural Networks

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2102.01792.

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

pith.paper-citation-record.v1
2102.01792 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 2026-08-23T06:30:58.430688+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:28:25.512758Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T15:21:36.810805Z

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 f5c291b7-0e21-434c-8149-4618d67896bb · inbound

Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders cites this paper.

Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders A Survey on Understanding, Visualizations, and Explanation of Deep Neural Networks

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-12T16:57:56.601133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:57:56.601133Z digest=sha256:de2cdad8cc8e649f4dc33b9532aa650e1181b06e84ea7331cb444988ae9b64e0

Observation 5be3d0fc-da4d-4ea4-a755-9c07b50f0d19 · inbound

CSMF: Cascaded Selective Mask Fine-Tuning for Multi-Objective Embedding-Based Retrieval cites this paper.

CSMF: Cascaded Selective Mask Fine-Tuning for Multi-Objective Embedding-Based Retrieval A Survey on Understanding, Visualizations, and Explanation of Deep Neural Networks

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-16T12:28:25.512758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:28:25.512758Z digest=sha256:4a9e85b1157edf1845373c8fe631644df481937a3a182021d3c1cb5805ab1835

Observation 25e7b3cf-37f0-47db-b0e7-b29d6ff58aa3 · inbound

Explainable embeddings with Distance Explainer cites this paper.

Explainable embeddings with Distance Explainer A Survey on Understanding, Visualizations, and Explanation of Deep Neural Networks

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:21:36.857094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-07T15:21:35.026765Z digest=sha256:a0f65e143acca3589ed7a09f4be55b9ee50404c134b0b30e59b41956c3adea32