Pith. sign in

Paper Citation Record · LEDGER

Vision Transformer with Sparse Scan Prior

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.13335.

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

pith.paper-citation-record.v1
2405.13335 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:04:29.713823Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:53:47.655533Z

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 f06efcc4-fd35-448f-91a4-da2750cd68f1 · inbound

Do we really have to filter out random noise in pre-training data for language models? cites this paper.

Do we really have to filter out random noise in pre-training data for language models? Vision Transformer with Sparse Scan Prior

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-08T15:04:29.713823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:04:29.713823Z digest=sha256:d9fe5081f385345d9230ee3ee0f2af0ed960b6174390379b699a8fb0cbaa5106

Observation 267252a0-8207-4b6c-802b-42630874524d · inbound

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling cites this paper.

HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling Vision Transformer with Sparse Scan Prior

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:53:47.733820Z

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.

source=pdf_text observed=2026-08-07T13:53:42.822060Z digest=sha256:3f2f6b9dc55ebf14677228e5fb5d5f09fc6da7bf50f68f7d916b8f42dcc141f8