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Paper Citation Record · LEDGER

Towards Galaxy Foundation Models with Hybrid Contrastive Learning

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.

pith.paper-citation-record.v1
2206.11927 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:52:56.449341Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T05:30:23.456663Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

14
pith, observed 2026-08-10T05:30:23.456663Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d0a45d15-d8c7-435f-9a0e-b32a5c676815 · inbound

From Galaxy Zoo DECaLS to BASS/MzLS: detailed galaxy morphology classification with unsupervised domain adaption cites this paper.

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

Resolution
unresolved
no resolver link, observed 2026-08-11T11:24:17.012832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:24:17.012832Z digest=sha256:e55e1668c8c72f46ec7cfb4c8377b358f5a34d9e48944c4301d551ba476b9a5a

Observation 2d8889da-12f8-4d8f-936e-dd389fceef4c · inbound

Are vision language models robust to uncertain inputs? cites this paper.

Are vision language models robust to uncertain inputs? Towards Galaxy Foundation Models with Hybrid Contrastive Learning

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-15T20:52:56.449341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:52:56.449341Z digest=sha256:b12961cfab2bcc8d1ebbe5108c4e098821e41761b760e75f99f2a50eaa48e1ff

Observation 45e53b79-0f17-4092-be15-51a0ecb2a27f · inbound

From stellar light to astrophysical insight: automating variable star research with machine learning cites this paper.

From stellar light to astrophysical insight: automating variable star research with machine learning Towards Galaxy Foundation Models with Hybrid Contrastive Learning

Reference 175

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T20:22:41.124380Z

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.

source=arxiv_source observed=2026-08-06T20:22:39.678055Z digest=sha256:d725f503f8433c1555b0dfea66cd452d4331bcb30b418456174ecd6e0c13ba94

Observation 4d928f2f-b725-4a7b-8f1d-aa89ed09a347 · inbound

Learning What's Real: Disentangling Signal and Measurement Artifacts in Multi-Sensor Data, with Applications to Astrophysics cites this paper.

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

Resolution
unresolved
no resolver link, observed 2026-07-12T23:05:33.283641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T23:05:33.283641Z digest=sha256:ef165ff7e845d9da5bbf926df91d1aaf4d1446d91b3a79463e39881f782230c4