Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Your other Left! Vision-Language Models Fail to Identify Relative Positions in Medical Images
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2508.00549.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-30T23:19:20.522732Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T13:25:45.168258Z
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 2a6a9526-2eca-4b08-8a47-984b2db5ce79 · inbound
Lost in Volume: The CT-SpatialVQA Benchmark for Evaluating Semantic-Spatial Understanding of 3D Medical Vision-Language Models cites this paper.
Lost in Volume: The CT-SpatialVQA Benchmark for Evaluating Semantic-Spatial Understanding of 3D Medical Vision-Language Models Your other Left! Vision-Language Models Fail to Identify Relative Positions in Medical Images
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:56:27.107419Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 9a20ae4c-0d66-4ffc-b8ed-b48a757a099d · inbound
Lost in Volume: The CT-SpatialVQA Benchmark for Evaluating Semantic-Spatial Understanding of 3D Medical Vision-Language Models cites this paper.
Lost in Volume: The CT-SpatialVQA Benchmark for Evaluating Semantic-Spatial Understanding of 3D Medical Vision-Language Models Your other Left! Vision-Language Models Fail to Identify Relative Positions in Medical Images
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T13:25:45.170237Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.