Paper Citation Record · LEDGER

Machine Learning with a Reject Option: A survey

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2107.11277.

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

pith.paper-citation-record.v1
2107.11277 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:45:43.576466Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T09:55:40.140387Z

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 0e4a2bd1-4a69-4243-86ff-23b1a7cd821a · inbound

Safety Monitoring of Machine Learning Perception Functions: a Survey cites this paper.

Safety Monitoring of Machine Learning Perception Functions: a Survey Machine Learning with a Reject Option: A survey

Reference 130

Resolution: unresolved; no resolver link, observed 2026-08-11T19:45:43.576466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dc1997f-8191-423c-b387-0249d5bb5556 · inbound

Conservative classifiers do consistently well with improving agents: characterizing statistical and online learning cites this paper.

Conservative classifiers do consistently well with improving agents: characterizing statistical and online learning Machine Learning with a Reject Option: A survey

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-07T10:35:39.503749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5294b28f-0947-4e2f-9482-2e1539964ee8 · inbound

Polyra Swarms: A Shape-Based Approach to Machine Learning cites this paper.

Polyra Swarms: A Shape-Based Approach to Machine Learning Machine Learning with a Reject Option: A survey

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:19.800537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f35b16c-0fc0-4bbe-973a-b72ab5219827 · inbound

Clustered Calibration: Representation-Aware Probability Calibration via Learned Subpopulations cites this paper.

Clustered Calibration: Representation-Aware Probability Calibration via Learned Subpopulations Machine Learning with a Reject Option: A survey

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T08:46:36.807955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd9c4246-bdbe-4da3-94e7-87cee3e151c5 · inbound

SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation cites this paper.

SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation Machine Learning with a Reject Option: A survey

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:22:09.021301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b26c5238-6731-4667-b0bd-8bda50ad6bbd · inbound

Expected Gain-based Escalation in Vertical Federated Learning cites this paper.

Expected Gain-based Escalation in Vertical Federated Learning Machine Learning with a Reject Option: A survey

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:55:40.142462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e5342e89-ad64-44ff-9851-fab61e5765ef · inbound

Removable Defects: The Economics and Limits of Deliberate Deficiency cites this paper.

Removable Defects: The Economics and Limits of Deliberate Deficiency Machine Learning with a Reject Option: A survey

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T07:00:25.920267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.