Paper Citation Record · LEDGER

Class-based Subset Selection for Transfer Learning under Extreme Label Shift

As of 15 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2501.00162.

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

pith.paper-citation-record.v1
2501.00162 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:05:46.572254Z

measured 15 of 15 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact1
verified fuzzy3
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 862307b1-5aa0-4650-ba01-3ca51fc0b7e1 · outbound

This paper cites an unresolved cited work.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:05:46.852720Z

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 34dd21b5-ef60-4021-8c92-042970e65fa5 · outbound

This paper cites The same color corresponds to the same class.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift The same color corresponds to the same class

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:46.819361Z

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 b81c904c-068a-40d1-81eb-231e68ad86ca · outbound

This paper cites Deep Domain Confusion: Maximizing for Domain Invariance.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Deep Domain Confusion: Maximizing for Domain Invariance

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T23:05:46.539222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00c9b7b7-3439-4dc0-8dbd-0078d81ca193 · outbound

This paper cites an unresolved cited work.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:05:46.836003Z

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 14bcfcfa-9a9f-48be-8898-41bc6b875197 · outbound

This paper cites an unresolved cited work.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:05:46.802806Z

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 fcdbc856-d286-4076-b5b1-7cc203a31544 · outbound

This paper cites an unresolved cited work.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Unresolved cited work

Reference 1991

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:05:46.920000Z

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 d3bf6bb5-408e-49e3-bc27-525ae9b2aa9d · outbound

This paper cites an unresolved cited work.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Unresolved cited work

Reference 2006

Resolution: unresolved; no resolver link, observed 2026-08-10T23:05:46.497157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d277f03f-0649-4681-a5b8-3131e5dc875a · outbound

This paper cites Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond

Reference 2009

Resolution: verified exact; local_arxiv, observed 2026-08-10T23:05:46.617490Z

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 4968096a-bca0-4472-8e13-2bd80ce1a550 · outbound

This paper cites Transferability in Deep Learning: A Survey.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Transferability in Deep Learning: A Survey

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-10T23:05:46.508637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95cf28d0-5a5f-4569-a224-e1ee3cf0661e · outbound

This paper cites Domain Adaptation: Learning Bounds and Algorithms.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Domain Adaptation: Learning Bounds and Algorithms

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-10T23:05:46.519155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1fc5a35-46cb-44db-90ee-4fea8716ca2d · outbound

This paper cites an unresolved cited work.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Unresolved cited work

Reference 2017

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:05:46.888216Z

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 9db5a708-3859-464e-9388-4020238fbe66 · outbound

This paper cites Mousavi Kalan, Z.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Mousavi Kalan, Z

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:46.904381Z

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 82548690-d500-40e4-9692-09890a0cb678 · outbound

This paper cites Fashion-MNISTisthesimplestdatasetwecon- sider containing 60, 000 train and 10, 000 test grayscale images of ten different clothing items.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Fashion-MNISTisthesimplestdatasetwecon- sider containing 60, 000 train and 10, 000 test grayscale images of ten different clothing items

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:05:46.870518Z

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 da69f695-8a59-4fe6-b863-7177155752a6 · outbound

This paper cites Zero-Shot Learning by Convex Combination of Semantic Embeddings.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Zero-Shot Learning by Convex Combination of Semantic Embeddings

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-10T23:05:46.529074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bffeb723-b607-46dd-9b43-8fdebb00c389 · outbound

This paper cites an unresolved cited work.

Class-based Subset Selection for Transfer Learning under Extreme Label Shift Unresolved cited work

Reference 2021

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:05:46.935775Z

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.

Pith citing papers

No inbound Pith citation observations are available.