Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
VisOnlyQA: Large Vision Language Models Still Struggle with Visual Perception of Geometric Information
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2412.00947.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T23:03:08.012180Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T03:06:30.214152Z
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 f4afe626-f042-4eb8-948c-6478f66f7fef · inbound
MathReal: We Keep It Real! A Real Scene Benchmark for Evaluating Math Reasoning in Multimodal Large Language Models cites this paper.
MathReal: We Keep It Real! A Real Scene Benchmark for Evaluating Math Reasoning in Multimodal Large Language Models VisOnlyQA: Large Vision Language Models Still Struggle with Visual Perception of Geometric Information
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T23:03:08.012180Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 830a32d2-05da-4338-85dc-07fca2b14c57 · inbound
Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models cites this paper.
Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models VisOnlyQA: Large Vision Language Models Still Struggle with Visual Perception of Geometric Information
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T08:15:51.700025Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c6fda004-17c1-49e6-a231-5e1f0f261a9f · inbound
Why MLLMs Struggle to Determine Object Orientations cites this paper.
Why MLLMs Struggle to Determine Object Orientations VisOnlyQA: Large Vision Language Models Still Struggle with Visual Perception of Geometric Information
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T10:46:04.546609Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 21f03969-e72a-430e-80f0-858351a178fa · inbound
State Beyond Appearance: Diagnosing and Improving State Consistency in Dial-Based Measurement Reading cites this paper.
State Beyond Appearance: Diagnosing and Improving State Consistency in Dial-Based Measurement Reading VisOnlyQA: Large Vision Language Models Still Struggle with Visual Perception of Geometric Information
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T09:16:26.557200Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4a1f0191-67c1-401c-a645-e41a857a2b47 · inbound
From Seeing to Thinking: Decoupling Perception and Reasoning Improves Post-Training of Vision-Language Models cites this paper.
From Seeing to Thinking: Decoupling Perception and Reasoning Improves Post-Training of Vision-Language Models VisOnlyQA: Large Vision Language Models Still Struggle with Visual Perception of Geometric Information
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T05:13:21.501063Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 7722e7a8-e3ed-4aec-be36-78b28d282a84 · inbound
A Dataset for Dynamic Human Preferences for Vision Language Models cites this paper.
A Dataset for Dynamic Human Preferences for Vision Language Models VisOnlyQA: Large Vision Language Models Still Struggle with Visual Perception of Geometric Information
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T03:06:30.233405Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.