Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
N-Grammer: Augmenting Transformers with latent n-grams
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2207.06366.
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 2026-08-06T20:31:47.940113Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, 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
6
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 3b78d1ba-6456-44db-820f-2801cdf63c95 · inbound
Fast and Simplex: 2-Simplicial Attention in Triton cites this paper.
Fast and Simplex: 2-Simplicial Attention in Triton N-Grammer: Augmenting Transformers with latent n-grams
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:31:47.940113Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33bf2d83-ad89-4aea-9060-6bf8aa7bb2e3 · inbound
Decoupling the Benefits of Subword Tokenization for Language Model Training via Byte-level Simulation cites this paper.
Decoupling the Benefits of Subword Tokenization for Language Model Training via Byte-level Simulation N-Grammer: Augmenting Transformers with latent n-grams
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T04:10:08.740419Z
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 97eafd81-ed5e-4fe8-920b-a215c943f402 · inbound
Decoupling the Benefits of Subword Tokenization for Language Model Training via Byte-level Simulation cites this paper.
Decoupling the Benefits of Subword Tokenization for Language Model Training via Byte-level Simulation N-Grammer: Augmenting Transformers with latent n-grams
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T06:59:49.082208Z
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.