Paper Citation Record · LEDGER

Towards Compositional Interpretability for XAI

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2406.17583.

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

pith.paper-citation-record.v1
2406.17583 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:41:04.951422Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4117dfff-a95c-4dc3-a47b-784ef462d45d · inbound

A Diagrammatic Approach to Improve Computational Efficiency in Group Equivariant Neural Networks cites this paper.

A Diagrammatic Approach to Improve Computational Efficiency in Group Equivariant Neural Networks Towards Compositional Interpretability for XAI

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-11T15:41:04.951422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d551dde1-f93b-4608-ad1c-1f3230c9a7ee · inbound

Towards a Comparative Framework for Compositional AI Models cites this paper.

Towards a Comparative Framework for Compositional AI Models Towards Compositional Interpretability for XAI

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T22:13:46.480784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12f5da98-1980-45f7-8046-5fdf0a30c9b7 · inbound

Bilinear autoencoders find interpretable manifolds cites this paper.

Bilinear autoencoders find interpretable manifolds Towards Compositional Interpretability for XAI

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-12T01:26:13.889388Z

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.

Observation 1fedaae5-e780-4f1e-b846-971e19b56ce6 · inbound

From Mechanistic to Compositional Interpretability cites this paper.

From Mechanistic to Compositional Interpretability Towards Compositional Interpretability for XAI

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:46:18.319514Z

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.

Observation 8a7345d0-96c6-4801-9abc-3a9df9ecd1b7 · inbound

The Standard Interpretable Model: A general theory of interpretable machine learning to deductively design interpretable methods using Lagrangian mechanics cites this paper.

The Standard Interpretable Model: A general theory of interpretable machine learning to deductively design interpretable methods using Lagrangian mechanics Towards Compositional Interpretability for XAI

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-03T08:17:45.542872Z

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.

Observation 3179bf61-48ca-4277-ae7d-fa7375ce58ba · inbound

When AI meets quantum information: A comprehensive review cites this paper.

When AI meets quantum information: A comprehensive review Towards Compositional Interpretability for XAI

Reference 217

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:46:56.296583Z

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.

Observation f64899e8-f982-49e4-ba63-8d1ef1fa5fca · inbound

Conversable Complexity: Agentic LLM Collectives as Interpretable Substrates cites this paper.

Conversable Complexity: Agentic LLM Collectives as Interpretable Substrates Towards Compositional Interpretability for XAI

Reference 93

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:46:56.212830Z

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.