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Paper Citation Record · LEDGER

Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.11261.

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

pith.paper-citation-record.v1
2410.11261 v2

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 2026-08-09T18:51:12.558692Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:36:28.975399Z

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 6a8dba0f-26dc-47ee-81fe-0e856ea6a27b · 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 Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-09T18:51:12.558692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:51:12.558692Z digest=sha256:2fae7dd70f2d1ab25ff2682e51824cd5b47758f1d9f3a933346f5ca89e9a888f

Observation b202b886-7f38-4158-a517-0a9045b4ddff · inbound

Universal Approximation of Visual Autoregressive Transformers cites this paper.

Universal Approximation of Visual Autoregressive Transformers Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-08T16:39:14.211419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T16:39:14.211419Z digest=sha256:d4107f158cdb6edc9478e642045c9461eb0a61f1729aa95bd291aabb6fad14df

Observation a6740093-4468-4bfb-98e9-ea5c20b7031a · inbound

LatentLLM: Attention-Aware Joint Tensor Compression cites this paper.

LatentLLM: Attention-Aware Joint Tensor Compression Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:36:29.038387Z

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=2026-08-07T14:36:26.765346Z digest=sha256:aaee8fe8cf95337c6aa4597975329570f5727bf542e3a85e0c3d806c7be7a1d6