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Paper Citation Record · LEDGER

Hierarchical Sparse Attention Framework for Computationally Efficient Classification of Biological Cells

As of 18 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 1 inbound Pith citation observation for arXiv:2505.07661.

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

pith.paper-citation-record.v1
2505.07661 v1

Coverage vector

measured 2 of 2 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:16:10.883897Z

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:48:04.613785Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T05:30:23.456663Z

Reference resolution

2 of 2 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
pith, observed 2026-08-10T05:30:23.456663Z

Outbound references

Observation fcd514cc-1fb4-4703-972c-6429b9b3f282 · outbound

This paper cites SampleNet: Differentiable Point Cloud Sampling.

Hierarchical Sparse Attention Framework for Computationally Efficient Classification of Biological Cells SampleNet: Differentiable Point Cloud Sampling

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-15T22:16:10.883897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:16:10.883897Z digest=sha256:64fff63716a87e12c58eef21c981ebfb692263c109222704cc3a43711e110915

Observation 5ef94bae-6e7f-4de6-ba6c-2c3b39bfcca6 · outbound

This paper cites 3D Semantic Segmentation with Submanifold Sparse Convolutional Networks.

Hierarchical Sparse Attention Framework for Computationally Efficient Classification of Biological Cells 3D Semantic Segmentation with Submanifold Sparse Convolutional Networks

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-15T22:16:10.878204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:16:10.878204Z digest=sha256:8af970000eca8d7382bbfbffff93f5cd09afe9671dbada06767321994dd67fba

Pith citing papers

Observation 1a799eef-9f63-4b9e-bddc-3a496f820c33 · inbound

PRISM: Distribution-Gated Flow Matching for Controllable Unpaired Image Translation cites this paper.

PRISM: Distribution-Gated Flow Matching for Controllable Unpaired Image Translation Hierarchical Sparse Attention Framework for Computationally Efficient Classification of Biological Cells

Reference 54

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:48:04.663266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T11:48:04.613785Z digest=sha256:547fac7c979a0ba814043f96062a4e9640cbd54a902472411f46d81436bd1eea