Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2010.02066.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T14:55:01.988432Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T17:37:57.270825Z
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 6b099cc3-2232-4000-819f-47c3cd3e1f91 · inbound
Interpretability in Parameter Space: Minimizing Mechanistic Description Length with Attribution-based Parameter Decomposition cites this paper.
Interpretability in Parameter Space: Minimizing Mechanistic Description Length with Attribution-based Parameter Decomposition Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T14:55:01.988432Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 64130377-6b92-4da4-96e5-08086e9abd8c · 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 Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T22:08:48.512966Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e213a17b-eece-4705-9848-25ce00051fd3 · inbound
From Indirect Object Identification to Syllogisms: Exploring Binary Mechanisms in Transformer Circuits cites this paper.
From Indirect Object Identification to Syllogisms: Exploring Binary Mechanisms in Transformer Circuits Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T17:37:57.351098Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.