Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2408.12664.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:40:55.305178Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T05:27:19.246521Z
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 48b7ea23-a93e-41a9-b6a6-562e195a25f0 · inbound
Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks cites this paper.
Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:40:55.305178Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a115375e-0a3f-466d-ad80-690f5d03daf1 · inbound
Representation biases: will we achieve complete understanding by analyzing representations? cites this paper.
Representation biases: will we achieve complete understanding by analyzing representations? Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T12:03:43.063552Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 57f004a6-e6f5-4913-b283-b727ca52088a · inbound
Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space cites this paper.
Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience
Reference 135
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T05:27:19.248264Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.