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Paper Citation Record · LEDGER

SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2111.13196.

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

pith.paper-citation-record.v1
2111.13196 v4

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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:20:44.449219Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T20:54:07.673279Z

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 cb158afd-4ddb-4e40-9d5c-d8ce68bbb667 · inbound

GIT: A Generative Image-to-text Transformer for Vision and Language cites this paper.

GIT: A Generative Image-to-text Transformer for Vision and Language SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioning

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-16T20:54:07.675223Z

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=2026-05-16T20:54:07.572136Z digest=sha256:c6017144ab7aceeb639ed951e455ace522c4d37389e5e0c20c39510c959b38e9

Observation f6b4739f-16a9-4b7c-8066-b9f4b34dc5a6 · inbound

MusiScene: Leveraging MU-LLaMA for Scene Imagination and Enhanced Video Background Music Generation cites this paper.

MusiScene: Leveraging MU-LLaMA for Scene Imagination and Enhanced Video Background Music Generation SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioning

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T19:20:44.449219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:20:44.449219Z digest=sha256:b43abf87713d847d319c3b08f2686736b8d60ce535a286ac55f78ba473ad2e94