Paper Citation Record · LEDGER

AgroGPT: Efficient Agricultural Vision-Language Model with Expert Tuning

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.08405.

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

pith.paper-citation-record.v1
2410.08405 v2

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 2026-08-23T06:30:58.430688+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:47:43.328677Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T09:44:37.149460Z

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 91aba2ca-557a-456d-afce-b3e4c4637c0f · inbound

Self-Consistency in Vision-Language Models for Precision Agriculture: Multi-Response Consensus for Crop Disease Management cites this paper.

Self-Consistency in Vision-Language Models for Precision Agriculture: Multi-Response Consensus for Crop Disease Management AgroGPT: Efficient Agricultural Vision-Language Model with Expert Tuning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T19:11:23.827224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70733eb8-f64a-4599-8a62-4d86461dd245 · inbound

AgroBench: Vision-Language Model Benchmark in Agriculture cites this paper.

AgroBench: Vision-Language Model Benchmark in Agriculture AgroGPT: Efficient Agricultural Vision-Language Model with Expert Tuning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T17:47:43.328677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7931bfc8-5044-432c-8eb5-b41b066482da · 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 AgroGPT: Efficient Agricultural Vision-Language Model with Expert Tuning

Reference 92

Resolution: verified exact; arxiv_id, observed 2026-05-19T02:06:58.731899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c50103cc-b2e6-49ec-8d49-93f4eab0d55e · inbound

Fine-Tuning General-Purpose Large Language Models for Agricultural Applications:A Reproducible Framework and Evaluation Protocol Based on Qwen3-8B cites this paper.

Fine-Tuning General-Purpose Large Language Models for Agricultural Applications:A Reproducible Framework and Evaluation Protocol Based on Qwen3-8B AgroGPT: Efficient Agricultural Vision-Language Model with Expert Tuning

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-30T09:44:37.151569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.