Paper Citation Record · LEDGER

When Source-Free Domain Adaptation Meets Learning with Noisy Labels

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2301.13381.

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

pith.paper-citation-record.v1
2301.13381 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:58:53.352211Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

20
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3aec5f1c-72cd-4d3d-8833-04c9f1104fe5 · inbound

Label Distribution Shift-Aware Prediction Refinement for Test-Time Adaptation cites this paper.

Label Distribution Shift-Aware Prediction Refinement for Test-Time Adaptation When Source-Free Domain Adaptation Meets Learning with Noisy Labels

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T16:58:53.352211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a96f661-3335-4421-978d-2af2b76c8903 · inbound

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation cites this paper.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation When Source-Free Domain Adaptation Meets Learning with Noisy Labels

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.417180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b335dcf8-bd8c-41c4-95bd-90184dfb0819 · inbound

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels cites this paper.

Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels When Source-Free Domain Adaptation Meets Learning with Noisy Labels

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T21:00:06.198994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fca863fd-d3c2-4b5a-be71-b93edbd22f8e · inbound

Unleashing the Power of Intermediate Domains for Mixed Domain Semi-Supervised Medical Image Segmentation cites this paper.

Unleashing the Power of Intermediate Domains for Mixed Domain Semi-Supervised Medical Image Segmentation When Source-Free Domain Adaptation Meets Learning with Noisy Labels

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T12:24:36.481851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c93758b-7ffd-42fb-9857-7faecd08f2e9 · inbound

Interact3D: Compositional 3D Generation of Interactive Objects cites this paper.

Interact3D: Compositional 3D Generation of Interactive Objects When Source-Free Domain Adaptation Meets Learning with Noisy Labels

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-13T23:59:14.441938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af822753-4edd-4f5f-acd0-edca95475657 · inbound

Rethinking the Need for Source Models: Source-Free Domain Adaptation from Scratch Guided by a Vision-Language Model cites this paper.

Rethinking the Need for Source Models: Source-Free Domain Adaptation from Scratch Guided by a Vision-Language Model When Source-Free Domain Adaptation Meets Learning with Noisy Labels

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-08T18:28:58.248077Z

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 b7c3c7f4-1951-4967-a678-446a793140fe · inbound

Safe-Subspace Pseudo-Label Refinement for Source-Free Graph Domain Adaptation cites this paper.

Safe-Subspace Pseudo-Label Refinement for Source-Free Graph Domain Adaptation When Source-Free Domain Adaptation Meets Learning with Noisy Labels

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T19:22:34.295195Z

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 a47c832a-fd51-46aa-9a24-22f12ee87cab · inbound

Full spectrum Unlearnable Examples via Spectral Equalization cites this paper.

Full spectrum Unlearnable Examples via Spectral Equalization When Source-Free Domain Adaptation Meets Learning with Noisy Labels

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:59:52.826755Z

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.