Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.05219.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:11:00.842439Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T23:04:15.294773Z
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 7810ca21-9f36-4c33-9a35-b3b10170829d · inbound
Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse cites this paper.
Only Large Weights (And Not Skip Connections) Can Prevent the Perils of Rank Collapse Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers
Reference 2016
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:11:00.842439Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 08d16313-d6e8-4b46-b21f-f399d5a5b7b0 · inbound
CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems cites this paper.
CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers
Reference 54
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T23:04:15.300198Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.