Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
As of 22 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1706.05806.
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 2026-07-20T06:30:07.809122+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-13T21:52:18.253648Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-10T06:15:00.866473Z
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 25daa382-0919-46a3-97c2-37ed41d80d8e · inbound
Understanding intermediate layers using linear classifier probes cites this paper.
Understanding intermediate layers using linear classifier probes SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T18:31:44.344603Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.
Observation db90d8fa-86dd-48f0-ad60-8f4a57acabf4 · inbound
SIMPLER: Efficient Foundation Model Adaptation via Similarity-Guided Layer Pruning for Earth Observation cites this paper.
SIMPLER: Efficient Foundation Model Adaptation via Similarity-Guided Layer Pruning for Earth Observation SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
Reference 30
- Resolution
- malformed identifier
- no resolver link, observed 2026-07-13T21:52:18.253648Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed44c3c1-5ae3-4808-8cb5-580d032b9568 · inbound
The Long Delay to Arithmetic Generalization: When Learned Representations Outrun Behavior cites this paper.
The Long Delay to Arithmetic Generalization: When Learned Representations Outrun Behavior SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-05-14T21:17:58.802813Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.
Observation 4f5ca09c-5b4f-4689-8cbd-191b42ff6e05 · inbound
When Are Two Networks the Same? Tensor Similarity for Mechanistic Interpretability cites this paper.
When Are Two Networks the Same? Tensor Similarity for Mechanistic Interpretability SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T03:19:43.712634Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.
Observation 01d13cf0-eca5-4674-8277-7413af19ddfa · inbound
From Layers to Networks: Comparing Neural Representations via Diffusion Geometry cites this paper.
From Layers to Networks: Comparing Neural Representations via Diffusion Geometry SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T20:03:43.664291Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.
Observation 57d07bf9-49f0-4247-ad51-a38b816b5f7c · inbound
Toy Combinatorial Interpretability Models Reveal Lottery Tickets in Early Feature Space cites this paper.
Toy Combinatorial Interpretability Models Reveal Lottery Tickets in Early Feature Space SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
Reference 68
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-19T22:12:50.975596Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.
Observation 077f2883-9027-4736-9773-644f9d6d0c50 · inbound
Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination cites this paper.
Graph-Native Reinforcement Learning Enables Traceable Scientific Hypothesis Generation through Conceptual Recombination SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
Reference 55
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-02T12:26:55.876176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-20T06:30:07.809122+00:00.