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Paper Citation Record · LEDGER

Space Rotation with Basis Transformation for Training-free Test-Time Adaptation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.19946.

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

pith.paper-citation-record.v1
2502.19946 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:43:28.436258Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T23:17:13.822076Z

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 6ea6480e-d7e0-4cca-81e8-0014b8c783b9 · inbound

Boosting Domain Incremental Learning: Selecting the Optimal Parameters is All You Need cites this paper.

Boosting Domain Incremental Learning: Selecting the Optimal Parameters is All You Need Space Rotation with Basis Transformation for Training-free Test-Time Adaptation

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T12:43:28.436258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:28.436258Z digest=sha256:4e4bb4ea444af4efaa8bf0e082123c6053e45207509acc710e27e29183acdc35

Observation 1146d894-dd32-4808-bce1-74cd2e199a46 · inbound

Adapting Vision-Language Models Without Labels: A Comprehensive Survey cites this paper.

Adapting Vision-Language Models Without Labels: A Comprehensive Survey Space Rotation with Basis Transformation for Training-free Test-Time Adaptation

Reference 219

Resolution
verified exact
local_arxiv, observed 2026-08-05T23:17:13.827724Z

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.

source=pdf_text observed=2026-08-05T23:17:07.305742Z digest=sha256:6646f8744db079c4c6fc8feedc1cacad22f7ca168fa3501ffb12b55aeeebbcbf