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Paper Citation Record · LEDGER

Edit3K: Universal Representation Learning for Video Editing Components

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.16048.

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

pith.paper-citation-record.v1
2403.16048 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 2026-08-04T06:34:03.388597+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T01:43:34.898639Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T01:46:14.008077Z

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 16ce4e47-0273-4b76-96b6-8306db8b588a · inbound

VEBench:Benchmarking Large Multimodal Models for Real-World Video Editing cites this paper.

VEBench:Benchmarking Large Multimodal Models for Real-World Video Editing Edit3K: Universal Representation Learning for Video Editing Components

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:11:13.468653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-08T01:30:19.531699Z digest=sha256:22e651dfdd5958b5ace7c573e47967ab0db79f8847daa275ee9246cf136a3c89

Observation 1eef172e-fe64-428e-8567-954c569f4741 · inbound

VEBench:Benchmarking Large Multimodal Models for Real-World Video Editing cites this paper.

VEBench:Benchmarking Large Multimodal Models for Real-World Video Editing Edit3K: Universal Representation Learning for Video Editing Components

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-12T01:46:14.009776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T01:43:34.898639Z digest=sha256:9ec413d1e34378e34c9e9cc9e039700e3c248fd788ca51cbf03d6a8d4e2f101e