Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Learning In-context n-grams with Transformers: Sub-n-grams Are Near-stationary Points
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2508.12837.
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 2026-08-02T10:12:29.129465Z
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
0
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 6175fb5c-89b1-40c8-a995-7fe76b38f892 · inbound
On the global convergence of gradient descent for wide shallow models with bounded nonlinearities cites this paper.
On the global convergence of gradient descent for wide shallow models with bounded nonlinearities Learning In-context n-grams with Transformers: Sub-n-grams Are Near-stationary Points
Reference 55
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T03:51:19.291387Z
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 60b03b04-346f-49ce-85f2-3a1766e2527b · inbound
Extracting Algorithms in Pre-trained LLMs: A Case on Hidden Markov Models cites this paper.
Extracting Algorithms in Pre-trained LLMs: A Case on Hidden Markov Models Learning In-context n-grams with Transformers: Sub-n-grams Are Near-stationary Points
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T10:12:29.129465Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.