Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Compute Better Spent: Replacing Dense Layers with Structured Matrices
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.06248.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T23:12:34.574522Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T15:26:33.712224Z
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 083707c7-711d-4f45-b87a-5e0fc4e79300 · inbound
DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models cites this paper.
DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models Compute Better Spent: Replacing Dense Layers with Structured Matrices
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:12:34.574522Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6a950f7e-474c-4ecb-9dbe-18605f675785 · inbound
Customizing the Inductive Biases of Softmax Attention using Structured Matrices cites this paper.
Customizing the Inductive Biases of Softmax Attention using Structured Matrices Compute Better Spent: Replacing Dense Layers with Structured Matrices
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T21:33:58.122029Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c9bf029d-6df7-426e-ad46-878e284b0229 · inbound
Low-rank surrogate modeling and stochastic zero-order optimization for training of neural networks with black-box layers cites this paper.
Low-rank surrogate modeling and stochastic zero-order optimization for training of neural networks with black-box layers Compute Better Spent: Replacing Dense Layers with Structured Matrices
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T15:26:33.717838Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.