Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2306.08173.
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 2026-08-07T05:47:29.878452Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T09:06:25.019701Z
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 fb32c6a1-87e3-443c-9f3f-38ba4225d358 · inbound
Dual-Priv Pruning : Efficient Differential Private Fine-Tuning in Multimodal Large Language Models cites this paper.
Dual-Priv Pruning : Efficient Differential Private Fine-Tuning in Multimodal Large Language Models Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:47:29.878452Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7dcb34c0-0ea8-4308-84d6-2953d6c19da1 · inbound
Differentially Private Contrastive Learning via Bounding Group-level Contribution cites this paper.
Differentially Private Contrastive Learning via Bounding Group-level Contribution Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T09:06:25.022537Z
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 731366d6-6860-4b75-89b7-9713c0cc022b · inbound
TrustCLIP: Learning Private Visual Features via Adversarial Reconstruction cites this paper.
TrustCLIP: Learning Private Visual Features via Adversarial Reconstruction Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T18:48:48.581852Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.