Paper Citation Record · LEDGER

Algorithmic Foundations of Empirical X-risk Minimization

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2206.00439.

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

pith.paper-citation-record.v1
2206.00439 v6

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 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:37:48.729494Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T04:56:38.672914Z

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 946caa97-b634-4073-a84d-4deaac628e1a · inbound

AASIST3: KAN-Enhanced AASIST Speech Deepfake Detection using SSL Features and Additional Regularization for the ASVspoof 2024 Challenge cites this paper.

AASIST3: KAN-Enhanced AASIST Speech Deepfake Detection using SSL Features and Additional Regularization for the ASVspoof 2024 Challenge Algorithmic Foundations of Empirical X-risk Minimization

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-23T21:33:28.481326Z

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 70c13e35-4da3-4350-8dce-114136c69a97 · inbound

Preserving AUC Fairness in Learning with Noisy Protected Groups cites this paper.

Preserving AUC Fairness in Learning with Noisy Protected Groups Algorithmic Foundations of Empirical X-risk Minimization

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T14:37:48.729494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65ac85a2-6f72-4910-929f-ced2d10fbdd3 · inbound

Exact Reformulation and Optimization for Direct Metric Optimization in Binary Imbalanced Classification cites this paper.

Exact Reformulation and Optimization for Direct Metric Optimization in Binary Imbalanced Classification Algorithmic Foundations of Empirical X-risk Minimization

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-06T15:43:28.483939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05d8c753-9b07-4b18-b658-ac7664cee750 · inbound

FairPOT: Balancing AUC Performance and Fairness with Proportional Optimal Transport cites this paper.

FairPOT: Balancing AUC Performance and Fairness with Proportional Optimal Transport Algorithmic Foundations of Empirical X-risk Minimization

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T01:01:43.185896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92ecb531-1d7e-4084-aa34-096b03aa36fb · inbound

Nonconvex Decentralized Stochastic Bilevel Optimization under Heavy-Tailed Noise cites this paper.

Nonconvex Decentralized Stochastic Bilevel Optimization under Heavy-Tailed Noise Algorithmic Foundations of Empirical X-risk Minimization

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-04T16:23:23.424626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1751dcb8-ec1b-459d-985c-8679f0e9feda · inbound

Enhancing Deep Neural Network Reliability with Refinement and Calibration cites this paper.

Enhancing Deep Neural Network Reliability with Refinement and Calibration Algorithmic Foundations of Empirical X-risk Minimization

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:56:38.677655Z

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.