Paper Citation Record · LEDGER

The Computational Complexity of Circuit Discovery for Inner Interpretability

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.08025.

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

pith.paper-citation-record.v1
2410.08025 v3

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 2026-08-21T06:32:19.484+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:25:05.518727Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T08:24:26.425433Z

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 ab7d45d5-d250-46c1-9d66-8e0aba5f0d49 · inbound

Towards Unified Attribution in Explainable AI, Data-Centric AI, and Mechanistic Interpretability cites this paper.

Towards Unified Attribution in Explainable AI, Data-Centric AI, and Mechanistic Interpretability The Computational Complexity of Circuit Discovery for Inner Interpretability

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T22:08:47.946408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d24f79fe-3978-4be5-8724-e0b428a1608f · inbound

Explain Yourself, Briefly! Self-Explaining Neural Networks with Concise Sufficient Reasons cites this paper.

Explain Yourself, Briefly! Self-Explaining Neural Networks with Concise Sufficient Reasons The Computational Complexity of Circuit Discovery for Inner Interpretability

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-09T04:59:50.573327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7be2a119-13da-4a7a-a1d7-649e3984d9d1 · inbound

Evaluating Explanations: An Explanatory Virtues Framework for Mechanistic Interpretability -- The Strange Science Part I.ii cites this paper.

Evaluating Explanations: An Explanatory Virtues Framework for Mechanistic Interpretability -- The Strange Science Part I.ii The Computational Complexity of Circuit Discovery for Inner Interpretability

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T04:25:05.518727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edd2d276-aeaf-4e1f-a1fb-aa437d2f821d · inbound

Reliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models cites this paper.

Reliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models The Computational Complexity of Circuit Discovery for Inner Interpretability

Reference 147

Resolution: verified exact; arxiv_id, observed 2026-06-30T08:24:26.427482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.