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Paper Citation Record · LEDGER

AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2502.01785.

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

pith.paper-citation-record.v1
2502.01785 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T18:28:55.336300Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T02:06:58.769990Z

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 835b0549-c4ff-4923-99f6-cd84e49684ec · inbound

AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock cites this paper.

AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-19T02:06:58.772657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T02:03:46.331803Z digest=sha256:65dee6f26456a85332dd12f6e97b2ad503e782797a1a55d2068be6455f8cac1a

Observation 3e79eda9-a4fc-43ff-abde-a0ccd1ac9cae · inbound

Label-efficient underwater species classification with logistic regression on frozen foundation model embeddings cites this paper.

Label-efficient underwater species classification with logistic regression on frozen foundation model embeddings AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:51:23.115841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T02:19:09.609298Z digest=sha256:53e8ad09e07e34895f335625794ad47e5e49277b693c7ccbb22b6a81116796d3

Observation 3f1cd8d7-5200-4278-aef5-7452f7ab6fd0 · inbound

Energy Constrained Hierarchical Underwater Monitoring via Local Multi-Agent RAG cites this paper.

Energy Constrained Hierarchical Underwater Monitoring via Local Multi-Agent RAG AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis

Reference 2

Resolution
unresolved
no resolver link, observed 2026-07-31T18:28:55.336300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T18:28:55.336300Z digest=sha256:caf7dc722fd85c5e266fc40a84214c03d4c89ad23396749a55b781fb509e0787