Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.13063.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T06:04:31.794356Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T06:04:36.417161Z
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 0ab7b6ac-76e4-4d48-ab73-0bd07d947043 · inbound
Cartridges: Lightweight and general-purpose long context representations via self-study cites this paper.
Cartridges: Lightweight and general-purpose long context representations via self-study Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity
Reference 49
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T06:04:36.422496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 47f6454c-b8a3-4a83-85b0-e449cf2e31ca · inbound
ARC-Encoder: learning compressed text representations for large language models cites this paper.
ARC-Encoder: learning compressed text representations for large language models Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T08:28:50.138327Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.