Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Spot Risks Before Speaking! Unraveling Safety Attention Heads in Large Vision-Language Models
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2501.02029.
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 2026-08-06T12:40:05.567271Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T21:55:52.621231Z
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 abf8391a-4cc4-47bd-bed3-db3c01ec31ea · inbound
Self-Aware Safety Augmentation: Leveraging Internal Semantic Understanding to Enhance Safety in Vision-Language Models cites this paper.
Self-Aware Safety Augmentation: Leveraging Internal Semantic Understanding to Enhance Safety in Vision-Language Models Spot Risks Before Speaking! Unraveling Safety Attention Heads in Large Vision-Language Models
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T12:40:05.567271Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2c4a8ed0-1635-4b35-ad3a-3e8feb02ff16 · inbound
Beyond Standard Benchmarks: A Systematic Audit of Vision-Language Model's Robustness to Natural Semantic Variation Across Diverse Tasks cites this paper.
Beyond Standard Benchmarks: A Systematic Audit of Vision-Language Model's Robustness to Natural Semantic Variation Across Diverse Tasks Spot Risks Before Speaking! Unraveling Safety Attention Heads in Large Vision-Language Models
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T21:55:52.623591Z
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 fba53fc4-82a2-42ab-8546-6cd5b542d37f · inbound
V-DEAL: Diagnosing Video Safety De-Calibration as an Understanding-Refusal Coupling Failure cites this paper.
V-DEAL: Diagnosing Video Safety De-Calibration as an Understanding-Refusal Coupling Failure Spot Risks Before Speaking! Unraveling Safety Attention Heads in Large Vision-Language Models
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T08:23:29.396060Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.