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Paper Citation Record · LEDGER

AgriGPT: a Large Language Model Ecosystem for Agriculture

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2508.08632.

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

pith.paper-citation-record.v1
2508.08632 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:27:11.066173Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:06:58.435348Z

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 435baef4-29c1-4237-a4f1-71433c8d7a9a · inbound

Towards AI Evaluation in Domain-Specific RAG Systems: The AgriHubi Case Study cites this paper.

Towards AI Evaluation in Domain-Specific RAG Systems: The AgriHubi Case Study AgriGPT: a Large Language Model Ecosystem for Agriculture

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-03T05:27:11.066173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:27:11.066173Z digest=sha256:88951dade6475a580cc17cb956ca745dabaaf65345924f04f0d875ca27b6c8fd

Observation 52d227c8-b38f-4c93-a8b2-31531080bd12 · inbound

From UAV Imagery to Agronomic Reasoning: A Multimodal LLM Benchmark for Plant Phenotyping cites this paper.

From UAV Imagery to Agronomic Reasoning: A Multimodal LLM Benchmark for Plant Phenotyping AgriGPT: a Large Language Model Ecosystem for Agriculture

Reference 21

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T07:25:59.793145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T17:11:50.265856Z digest=sha256:c415a052fe9617202e4c7b713547ffcb6347af10c6d3090faa42bbec3eb5f201

Observation dab3df87-f946-4c12-9c4b-fab5c93aa875 · inbound

Pest-Thinker: Learning to Think and Reason like Entomologists via Reinforcement Learning cites this paper.

Pest-Thinker: Learning to Think and Reason like Entomologists via Reinforcement Learning AgriGPT: a Large Language Model Ecosystem for Agriculture

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:46:09.461228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-08T14:02:29.480442Z digest=sha256:147ce4685f30d0bbdc08da3afb7bf4d043e7324b6b1adc14b5958c27400e9490

Observation 3f047709-0246-4fdd-83e8-1358ed46b00b · inbound

Hallucination Behavior in Multimodal LLMs Across Agricultural Image Interpretation and Generation Tasks cites this paper.

Hallucination Behavior in Multimodal LLMs Across Agricultural Image Interpretation and Generation Tasks AgriGPT: a Large Language Model Ecosystem for Agriculture

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-06-29T18:23:50.921746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T18:15:34.055839Z digest=sha256:68ede2cc8a278f852a805066ff6246a2e3d726beae7a74d4089911c1612924cb

Observation d59b7f5a-582c-44f2-8eca-131d5f7c79cd · 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 AgriGPT: a Large Language Model Ecosystem for Agriculture

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-06-30T09:44:37.147242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-30T09:44:26.234613Z digest=sha256:43975a0e82f8bc63f69f320fe20819a22f29f82647ddabfe8033ebf1a62b545d

Observation 457b87ae-eb11-492f-a75d-d5fc921690c2 · inbound

KrishokChat: A Citation-Grounded Dataset and Benchmark for Bengali Agricultural Advisory cites this paper.

KrishokChat: A Citation-Grounded Dataset and Benchmark for Bengali Agricultural Advisory AgriGPT: a Large Language Model Ecosystem for Agriculture

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:34:27.477721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-30T08:30:26.794528Z digest=sha256:08590afeb61a86965683d9b3b5627daa39bf24487c414df5418fcb3a19679392

Observation 68178682-78dd-42dd-b545-2818a0e541c7 · inbound

Agri-SAGE: Simulation-Grounded Multi-Agent LLM for Context-Aware Agricultural Advisory Generation cites this paper.

Agri-SAGE: Simulation-Grounded Multi-Agent LLM for Context-Aware Agricultural Advisory Generation AgriGPT: a Large Language Model Ecosystem for Agriculture

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-02T13:06:58.436996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-07-02T13:05:02.609607Z digest=sha256:d5e20e5406fca84f3e0e37de1dd9cce75d93750aa796ac9326d0eaf3c003d896