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Paper Citation Record · LEDGER

AgMMU: A Comprehensive Agricultural Multimodal Understanding Benchmark

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2504.10568.

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

pith.paper-citation-record.v1
2504.10568 v2

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:21:43.247071Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:59:42.846414Z

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 0d103b60-efe5-4780-ba66-3cf91b36c0a7 · inbound

Towards Large Reasoning Models for Agriculture cites this paper.

Towards Large Reasoning Models for Agriculture AgMMU: A Comprehensive Agricultural Multimodal Understanding Benchmark

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T14:21:43.247071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:21:43.247071Z digest=sha256:454ade0613ad462a28a4454e4006bb75ad5e1d36bdbcdd18b1630b78862f3054

Observation 1aa22337-fbc6-417f-a0e1-729da0322a3f · inbound

Benchmarking Vision-Language Models for Microscopic Plant Image Understanding cites this paper.

Benchmarking Vision-Language Models for Microscopic Plant Image Understanding AgMMU: A Comprehensive Agricultural Multimodal Understanding Benchmark

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:59:42.848321Z

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=2026-06-26T10:42:28.698142Z digest=sha256:dbe9e4f930a96679cbf17894172cd0b01fe3263fcf5fccd412ae866412827812