Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2206.11927.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:52:56.449341Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T05:30:23.456663Z
0 of 0 outbound references displayed
External citation measurements
14
pith, observed 2026-08-10T05:30:23.456663Z
No outbound reference observations are available for this paper version.
Observation d0a45d15-d8c7-435f-9a0e-b32a5c676815 · inbound
From Galaxy Zoo DECaLS to BASS/MzLS: detailed galaxy morphology classification with unsupervised domain adaption Towards Galaxy Foundation Models with Hybrid Contrastive Learning
Reference 51
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2d8889da-12f8-4d8f-936e-dd389fceef4c · inbound
Are vision language models robust to uncertain inputs? Towards Galaxy Foundation Models with Hybrid Contrastive Learning
Reference 62
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 45e53b79-0f17-4092-be15-51a0ecb2a27f · inbound
From stellar light to astrophysical insight: automating variable star research with machine learning Towards Galaxy Foundation Models with Hybrid Contrastive Learning
Reference 175
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4d928f2f-b725-4a7b-8f1d-aa89ed09a347 · inbound
Learning What's Real: Disentangling Signal and Measurement Artifacts in Multi-Sensor Data, with Applications to Astrophysics Towards Galaxy Foundation Models with Hybrid Contrastive Learning
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.