Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Tensor network compressibility of convolutional models
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2403.14379.
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 2026-08-07T14:01:56.847342Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-24T06:29:00.647295Z
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 b49239e5-4a70-4bf4-99b3-a3b3fdb6046f · inbound
Efficient Finite Initialization with Partial Norms for Tensorized Neural Networks and Tensor Networks Algorithms cites this paper.
Efficient Finite Initialization with Partial Norms for Tensorized Neural Networks and Tensor Networks Algorithms Tensor network compressibility of convolutional models
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T06:29:00.651194Z
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.
Observation b90ff0e6-6803-4e5d-8d13-4316a1ce647d · inbound
Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks cites this paper.
Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks Tensor network compressibility of convolutional models
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:01:56.847342Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6dba08cb-0d1f-4755-920a-2607179f7aaf · inbound
Fast Tensorization of Neural Networks via Slice-wise Feature Distillation cites this paper.
Fast Tensorization of Neural Networks via Slice-wise Feature Distillation Tensor network compressibility of convolutional models
Reference 45
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-20T06:53:22.944956Z
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.