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Paper Citation Record · LEDGER

Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2304.02207.

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

pith.paper-citation-record.v1
2304.02207 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:51:12.335719Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-17T18:00:50.269699Z

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 c20b00c4-9a48-4ab4-958e-49065139ff25 · inbound

H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models cites this paper.

H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-05-17T18:00:50.272467Z

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.

source=pdf_text observed=2026-05-17T18:00:50.053377Z digest=sha256:9aef6fbcd4ce7f54f775138065dd41a3fb514466f1ca5bba2d39b3a4089c3490

Observation 4c6160c4-d3c4-4439-a760-9e807a3fd8a0 · inbound

Video Latent Flow Matching: Optimal Polynomial Projections for Video Interpolation and Extrapolation cites this paper.

Video Latent Flow Matching: Optimal Polynomial Projections for Video Interpolation and Extrapolation Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-09T18:51:12.335719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:51:12.335719Z digest=sha256:6733775a52b6303799fce6b1cf1f4231ee136f88e21bce5251a7655fba3b5803

Observation 0b4b1022-fedd-4ef0-99b3-892349274850 · inbound

Subquadratic Algorithms and Hardness for Attention with Any Temperature cites this paper.

Subquadratic Algorithms and Hardness for Attention with Any Temperature Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T15:42:51.308081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:42:51.308081Z digest=sha256:1b79683341c77bb0636f95d57d9168376a5277c274c1ac4fd83896dffce345e2