Paper Citation Record · LEDGER

N-Grammer: Augmenting Transformers with latent n-grams

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2207.06366.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2207.06366 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T05:28:04.853919Z

measured 1 of 1 external citation measurements

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 264db988-6319-45d6-94d3-6f3bc3a151b2 · inbound

Over-Tokenized Transformer: Vocabulary is Generally Worth Scaling cites this paper.

Over-Tokenized Transformer: Vocabulary is Generally Worth Scaling N-Grammer: Augmenting Transformers with latent n-grams

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T05:28:04.853919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-13T06:32:02.005865+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 2026-08-13T06:32:02.005865+00:00.