Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2310.06549.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:48:42.770842Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T23:54:27.797173Z
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 0e62e35e-f764-4efe-96e0-8aa6638498f1 · inbound
How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference cites this paper.
How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:48:42.770842Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 854a65eb-1f83-4532-9178-0328e2bba8f3 · inbound
Deep Learning Model Inversion Attacks and Defenses: A Comprehensive Survey cites this paper.
Deep Learning Model Inversion Attacks and Defenses: A Comprehensive Survey Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
Reference 115
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T21:58:41.445372Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd6f016c-9c54-47c1-ad39-60be8aa11f38 · inbound
Partitioning for Intrinsic Model Inversion Resistance in Collaborative Inference cites this paper.
Partitioning for Intrinsic Model Inversion Resistance in Collaborative Inference Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T23:54:27.800446Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.