Paper Citation Record · LEDGER

Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1906.10908.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1906.10908 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:58:38.974307Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-20T21:43:45.492629Z

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 7badc905-23d0-4547-bcaf-3cb700ec9ffd · inbound

Bounding-box Watermarking: Defense against Model Extraction Attacks on Object Detectors cites this paper.

Bounding-box Watermarking: Defense against Model Extraction Attacks on Object Detectors Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T16:58:38.974307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65aca9c0-a9e8-4ee8-93e7-fbd27e69b3f9 · inbound

MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models cites this paper.

MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T11:29:46.552480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4eaa4d3b-b038-4d39-a7d9-f21b26a69a06 · inbound

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives cites this paper.

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks

Reference 156

Resolution: unresolved; no resolver link, observed 2026-08-05T18:12:37.597056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2666945b-f3e6-4736-9065-2565a9810e33 · inbound

On the (In-)Security of the Shuffling Defense in the Transformer Secure Inference cites this paper.

On the (In-)Security of the Shuffling Defense in the Transformer Secure Inference Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks

Reference 170

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:36:06.562779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7279caf3-dfba-4505-aad5-aa439fa3b8e8 · inbound

Lossless Anti-Distillation Sampling cites this paper.

Lossless Anti-Distillation Sampling Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks

Reference 106

Resolution: verified exact; arxiv_id, observed 2026-05-20T21:43:45.494460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ae3fd64b-c402-48bc-bb9b-3970dddf2595 · inbound

ADS-C: Antidistillation Sampling for Classification cites this paper.

ADS-C: Antidistillation Sampling for Classification Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-01T23:20:44.211113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.