Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2004.09031.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-10T01:58:58.772489Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
5
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation b9c16a37-275d-4f87-bff9-ae77518158ec · inbound
Spectral Compact Training: Pre-Training Large Language Models via Permanent Truncated SVD and Stiefel QR Retraction cites this paper.
Spectral Compact Training: Pre-Training Large Language Models via Permanent Truncated SVD and Stiefel QR Retraction Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T22:58:24.103977Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 126f7624-4c67-4286-b646-fa691666b396 · inbound
SigmaScale: LLM Compression with SVD-based Low-Rank Decomposition and Learned Scaling Matrices cites this paper.
SigmaScale: LLM Compression with SVD-based Low-Rank Decomposition and Learned Scaling Matrices Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-06-27T22:11:20.838173Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 013c8d2e-4f52-44a6-ad81-5c61d8349a3f · inbound
SLORR: Simple and Efficient In-Training Low-Rank Regularization cites this paper.
SLORR: Simple and Efficient In-Training Low-Rank Regularization Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification
Reference 7
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-10T02:06:42.167871Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.