Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.01352.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T14:02:12.825929Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T12:35:43.101025Z
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 3cc8445b-3399-4f16-b931-3e5519e53922 · inbound
Propositional Interpretability in Artificial Intelligence cites this paper.
Propositional Interpretability in Artificial Intelligence Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T14:02:12.825929Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 40c8db46-091a-44f9-a79e-514c8786c25a · 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 Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience
Reference 96
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T22:08:49.479518Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae35ad49-f82c-40b3-a740-616edf723077 · inbound
Circuit Stability Characterizes Language Model Generalization cites this paper.
Circuit Stability Characterizes Language Model Generalization Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience
Reference 57
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T12:35:43.211999Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.