Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
From Visual Prompt Learning to Zero-Shot Transfer: Mapping Is All You Need
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2303.05266.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T21:01:26.943285Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T19:56:11.267643Z
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 4be5a6ce-df0c-47ec-ad7d-c06c77d95c8f · inbound
Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design cites this paper.
Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design From Visual Prompt Learning to Zero-Shot Transfer: Mapping Is All You Need
Reference 74
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T21:01:26.943285Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4066e49c-cdbe-457d-8fcb-d1fec1c1d0bc · inbound
Visual prompting reimagined: The power of the Activation Prompts cites this paper.
Visual prompting reimagined: The power of the Activation Prompts From Visual Prompt Learning to Zero-Shot Transfer: Mapping Is All You Need
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:45:53.779837Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d0d9d0da-d759-4eff-98f5-0909922b047e · inbound
BadBone: Backdoor Attacks Against Backbone Models in Visual Prompt Learning cites this paper.
BadBone: Backdoor Attacks Against Backbone Models in Visual Prompt Learning From Visual Prompt Learning to Zero-Shot Transfer: Mapping Is All You Need
Reference 68
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T19:56:11.269323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.