Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Generating More Pertinent Captions by Leveraging Semantics and Style on Multi-Source Datasets
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2111.12727.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T05:51:15.918167Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T20:54:07.622646Z
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 1c6f4223-f62f-46a5-b315-f09142c86efe · 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 Generating More Pertinent Captions by Leveraging Semantics and Style on Multi-Source Datasets
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T20:54:07.624686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 09cd8215-1680-48de-993a-e4103b1646ff · inbound
CogVLM: Visual Expert for Pretrained Language Models cites this paper.
CogVLM: Visual Expert for Pretrained Language Models Generating More Pertinent Captions by Leveraging Semantics and Style on Multi-Source Datasets
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T15:46:06.472683Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 36ba18d9-dc18-4cb0-b269-95216a259cdd · inbound
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models cites this paper.
Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models Generating More Pertinent Captions by Leveraging Semantics and Style on Multi-Source Datasets
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T05:51:15.918167Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.