Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Internal Activation Revision: Safeguarding Vision Language Models Without Parameter Update
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2501.16378.
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 2026-08-07T14:13:12.116754Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T12:09:40.113596Z
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 f733c6bc-5689-4c0c-bdf6-a59b0f3081f7 · inbound
VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration cites this paper.
VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration Internal Activation Revision: Safeguarding Vision Language Models Without Parameter Update
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:13:12.116754Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5fc42ab4-9d73-4090-8170-d4529d5ba78d · 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 Internal Activation Revision: Safeguarding Vision Language Models Without Parameter Update
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T12:40:05.341720Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1126559f-21f4-4e64-83a8-bb3d8b427c5d · inbound
Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security cites this paper.
Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Internal Activation Revision: Safeguarding Vision Language Models Without Parameter Update
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T12:09:40.121101Z
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.