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Paper Citation Record · LEDGER

LPViT: Low-Power Semi-structured Pruning for Vision Transformers

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.02068.

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

pith.paper-citation-record.v1
2407.02068 v5

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 2026-08-10T14:46:38.245641Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T07:40:43.939320Z

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 c0f32fd0-4f4a-40ab-b7bb-cdce41df1f39 · inbound

On Accelerating Edge AI: Optimizing Resource-Constrained Environments cites this paper.

On Accelerating Edge AI: Optimizing Resource-Constrained Environments LPViT: Low-Power Semi-structured Pruning for Vision Transformers

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-10T14:46:38.245641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:46:38.245641Z digest=sha256:69f5f2f811841b285b1cfbc68afeb05d37a216ace7e1d1d417868283e6d2d18f

Observation e63ac3ac-d32b-4e3f-adbe-a5ed41754ca7 · inbound

CORP: Closed-Form One-shot Representation-Preserving Structured Pruning for Transformers cites this paper.

CORP: Closed-Form One-shot Representation-Preserving Structured Pruning for Transformers LPViT: Low-Power Semi-structured Pruning for Vision Transformers

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-16T07:40:43.941052Z

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=2026-05-16T07:38:50.252917Z digest=sha256:9519354b808f7b4af7b5c1a945dba6cd21ae852784bb222beb38ffc24de74349

Observation 13c9a042-2ecf-44db-baa1-44ba71f226c9 · inbound

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective cites this paper.

Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective LPViT: Low-Power Semi-structured Pruning for Vision Transformers

Reference 84

Resolution
unresolved
no resolver link, observed 2026-07-11T23:58:47.097757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T23:58:47.097757Z digest=sha256:146c6a243ebd674af64ca26f36671f24c1617e4dbc461132d65f0b994d6ba926