Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Probing Image-Language Transformers for Verb Understanding
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2106.09141.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T04:37:09.644104Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T16:21:36.477879Z
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 bf8c7b70-2d00-44d5-886a-5f08865214a8 · inbound
Kronecker Mask and Interpretive Prompts are Language-Action Video Learners cites this paper.
Kronecker Mask and Interpretive Prompts are Language-Action Video Learners Probing Image-Language Transformers for Verb Understanding
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T04:37:09.644104Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 177fad96-974e-474e-9b39-9f75b9d9a461 · inbound
A Good CREPE needs more than just Sugar: Investigating Biases in Compositional Vision-Language Benchmarks cites this paper.
A Good CREPE needs more than just Sugar: Investigating Biases in Compositional Vision-Language Benchmarks Probing Image-Language Transformers for Verb Understanding
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:21:35.003872Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1782759a-7914-4003-aa50-63b0dcad429e · inbound
Unveiling the Response of Large Vision-Language Models to Visually Absent Tokens cites this paper.
Unveiling the Response of Large Vision-Language Models to Visually Absent Tokens Probing Image-Language Transformers for Verb Understanding
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T11:15:19.644943Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 15b44022-7957-458a-960f-75c25060bfaf · inbound
V-SEAM: Visual Semantic Editing and Attention Modulating for Causal Interpretability of Vision-Language Models cites this paper.
V-SEAM: Visual Semantic Editing and Attention Modulating for Causal Interpretability of Vision-Language Models Probing Image-Language Transformers for Verb Understanding
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T16:21:36.481429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 7b0f3be6-5957-4ccf-8826-e05938a698ef · inbound
HNC: Leveraging Hard Negative Captions towards Models with Fine-Grained Visual-Linguistic Comprehension Capabilities cites this paper.
HNC: Leveraging Hard Negative Captions towards Models with Fine-Grained Visual-Linguistic Comprehension Capabilities Probing Image-Language Transformers for Verb Understanding
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T18:11:06.639388Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.