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Paper Citation Record · LEDGER

VLAB: Enhancing Video Language Pre-training by Feature Adapting and Blending

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.13167.

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

pith.paper-citation-record.v1
2305.13167 v1

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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:02:28.118849Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T06:30:22.640312Z

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 7e688be5-ca48-41f7-aeaf-ac5f652c5230 · inbound

InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation cites this paper.

InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation VLAB: Enhancing Video Language Pre-training by Feature Adapting and Blending

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-15T06:30:22.643920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T06:30:22.431538Z digest=sha256:7131490b5e28732babfdde58a05778caa8e7f3b07e223d38ccf0637800aaf37e

Observation b6247258-8cda-4e7a-a7c6-2fc1cfed444c · inbound

Temporal Object Captioning for Street Scene Videos from LiDAR Tracks cites this paper.

Temporal Object Captioning for Street Scene Videos from LiDAR Tracks VLAB: Enhancing Video Language Pre-training by Feature Adapting and Blending

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T15:02:28.118849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:02:28.118849Z digest=sha256:7df9d7571410a5cdd60c739a8709ba2e09fa08ab13f8b5f6bba0d19fbfc460fa