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Paper Citation Record · LEDGER

Keyframe-oriented Vision Token Pruning: Enhancing Efficiency of Large Vision Language Models on Long-Form Video Processing

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2503.10742.

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

pith.paper-citation-record.v1
2503.10742 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 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:46:40.634003Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:26:17.425104Z

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 9076d24e-6443-43b6-b77b-68b867bead47 · inbound

Video-MMLU: A Massive Multi-Discipline Lecture Understanding Benchmark cites this paper.

Video-MMLU: A Massive Multi-Discipline Lecture Understanding Benchmark Keyframe-oriented Vision Token Pruning: Enhancing Efficiency of Large Vision Language Models on Long-Form Video Processing

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-16T11:46:40.634003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:46:40.634003Z digest=sha256:471ff1f24ac9adcd68e999569b2641e8bc3ab215cb87691713f45e05a92cb653

Observation 847a243a-9c9c-4f22-89d6-eae1454cc240 · inbound

CoreMatching: A Co-adaptive Sparse Inference Framework with Token and Neuron Pruning for Comprehensive Acceleration of Vision-Language Models cites this paper.

CoreMatching: A Co-adaptive Sparse Inference Framework with Token and Neuron Pruning for Comprehensive Acceleration of Vision-Language Models Keyframe-oriented Vision Token Pruning: Enhancing Efficiency of Large Vision Language Models on Long-Form Video Processing

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:26:17.428918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:26:17.230770Z digest=sha256:1e16f9ec271c813afa735818b5597c7107030ffb2b04ae4435b382080bb8541e

Observation 36ab5eab-e8a1-4743-be8b-341464b3e9c5 · inbound

Development of Vision-Language Model-based GNSS Spoofing Detection for Autonomous Vehicle Navigation cites this paper.

Development of Vision-Language Model-based GNSS Spoofing Detection for Autonomous Vehicle Navigation Keyframe-oriented Vision Token Pruning: Enhancing Efficiency of Large Vision Language Models on Long-Form Video Processing

Reference 2

Resolution
unresolved
no resolver link, observed 2026-07-31T23:29:18.238729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:29:18.238729Z digest=sha256:498668b1f806193830347aa942ce36a63732f29213c14f02515452487ded8d6c