Paper Citation Record · LEDGER

Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1804.00308.

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

pith.paper-citation-record.v1
1804.00308 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:51:14.295549Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T20:26:29.754577Z

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 83d3bb4b-3e36-4d8c-887e-877c046349dc · inbound

Algorithmic Complexity Attacks on All Learned Cardinality Estimators: A Data-centric Approach cites this paper.

Algorithmic Complexity Attacks on All Learned Cardinality Estimators: A Data-centric Approach Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T18:51:14.295549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16240877-03e0-4d4b-8e0f-06aa324c2e97 · inbound

RAG-Pull: Turning Retrieval into a Code-Injection Channel via Invisible Unicode Perturbations cites this paper.

RAG-Pull: Turning Retrieval into a Code-Injection Channel via Invisible Unicode Perturbations Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-25T08:05:31.207031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5ee26bab-4aa0-41f1-bdef-c5d55b454c5f · inbound

Enabling Adversarial Robustness in AI Models through Kubeflow MLOps cites this paper.

Enabling Adversarial Robustness in AI Models through Kubeflow MLOps Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T16:32:39.430183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6f3da40f-36a0-4b1b-95d7-67ba57b532fe · inbound

Structural Adversarial Attacks on Relational Deep Learning under Integrity Constraints cites this paper.

Structural Adversarial Attacks on Relational Deep Learning under Integrity Constraints Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-09T20:26:29.755833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.