mlsanityData to 7 Oct 2026

Agricultural vision-language models

42 papers0 this weekHigh confidence in this grouping: the papers form one clear topicHigh confidence in this grouping: the papers form one clear topic · About

Keywords: agricultural, plant, agriculture, species, disease

Key facts. Agricultural vision-language models: 42 papers on arXiv since 2023 (data through 7 Oct 2026). 9 of its 42 mapped papers (21%) cite “AgroGPT: Efficient Agricultural Vision-Language Model with Expert Tuning” (2024, arXiv 2410.08405). 9 of its 42 mapped papers (21%) cite “AgroBench: Vision-Language Model Benchmark in Agriculture” (2025, arXiv 2507.20519). 1 new paper 17 Sep–7 Oct.

What’s new

17 Sep – 7 Oct 2026

1 new since 17 Sep

  1. A Vision-Language Model (VLM)-based Pipeline for End-to-End Procedural Modeling of Field-Grown Maize from Point Clouds

Foundations

Most cited by papers here

  1. AgroGPT: Efficient Agricultural Vision-Language Model with Expert Tuning2024cited by 9 here
  2. AgroBench: Vision-Language Model Benchmark in Agriculture2025cited by 9 here
  3. Leveraging Vision Language Models for Specialized Agricultural Tasks2024cited by 5 here
  4. AgMMU: A Comprehensive Agricultural Multimodal Understanding Benchmark2025cited by 5 here
  5. AgriCLIP: Adapting CLIP for Agriculture and Livestock via Domain-Specialized Cross-Model Alignment2024cited by 4 here

Lineage

The papers this direction builds on, oldest first.

Each paper on the line cites the one before.

  1. 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generationcited by 4 here
  2. 2022Flamingo: a Visual Language Model for Few-Shot Learningcited by 10 here
  3. 2023InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuningcited by 3 here
  4. 2023GLaMM: Pixel Grounding Large Multimodal Modelcited by 2 here
  5. 2024AgroGPT: Efficient Agricultural Vision-Language Model with Expert Tuningcited by 9 here
  6. 2025AgroBench: Vision-Language Model Benchmark in Agriculturecited by 9 here
18 more it builds on, not in this chain
  1. 2021CLIP-Adapter: Better Vision-Language Models with Feature Adapterscited by 2 here
  2. 2023A Survey on Multimodal Large Language Modelscited by 3 here
  3. 2023MMBench: Is Your Multi-modal Model an All-around Player?cited by 2 here
  4. 2023A Systematic Survey of Prompt Engineering on Vision-Language Foundation Modelscited by 2 here
  5. 2023MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilitiescited by 2 here
  6. 2023Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyondcited by 6 here
  7. 2023MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contextscited by 2 here
  8. 2023Improved Baselines with Visual Instruction Tuningcited by 9 here
  9. 2023Compositional Chain-of-Thought Prompting for Large Multimodal Modelscited by 2 here
  10. 2023GSVA: Generalized Segmentation via Multimodal Large Language Modelscited by 2 here
  11. 2023BloomVQA: Assessing Hierarchical Multi-modal Comprehensioncited by 2 here
  12. 2023InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Taskscited by 2 here
  13. 2024PaliGemma: A versatile 3B VLM for transfercited by 2 here
  14. 2024Leveraging Vision Language Models for Specialized Agricultural Taskscited by 5 here
  15. 2024LLaVA-OneVision: Easy Visual Task Transfercited by 3 here
  16. 2024AgriCLIP: Adapting CLIP for Agriculture and Livestock via Domain-Specialized Cross-Model Alignmentcited by 4 here
  17. 2025AgMMU: A Comprehensive Agricultural Multimodal Understanding Benchmarkcited by 5 here
  18. 2025AgriGPT-VL: Agricultural Vision-Language Understanding Suitecited by 3 here

The 24 most cited of 112.

Browse

30 of 42, ranked 6–35

  1. 6AgriGPT-VL: Agricultural Vision-Language Understanding Suite20253
  2. 7Harnessing Large Vision and Language Models in Agriculture: A Review20242
  3. 8LeafNet: A Large-Scale Dataset and Comprehensive Benchmark for Foundational Vision-Language Understanding of Plant Diseases20261
  4. 9Self-Consistency in Vision-Language Models for Precision Agriculture: Multi-Response Consensus for Crop Disease Management20251
  5. 10PlantExpertVQA: A Visual Question Answering Dataset for Benchmarking Vision-Language Models in Plant Science20251
  6. 11VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images20241
  7. 12AgriBench: A Hierarchical Agriculture Benchmark for Multimodal Large Language Models20241
  8. 13MAviS: A Multimodal Conversational Assistant For Avian Species20260
  9. 14Using Vision Language Foundation Models to Generate Plant Simulation Configurations via In-Context Learning20260
  10. 15Look Where It Matters: High-Resolution Crops Retrieval for Efficient VLMs20260
All 30
  1. 16AgriChat: A Multimodal Large Language Model for Agriculture Image Understanding20260
  2. 17AgriChain Visually Grounded Expert Verified Reasoning for Interpretable Agricultural Vision Language Models20260
  3. 18From UAV Imagery to Agronomic Reasoning: A Multimodal LLM Benchmark for Plant Phenotyping20260
  4. 19Thinking Like a Botanist: Challenging Multimodal Language Models with Intent-Driven Chain-of-Inquiry20260
  5. 20CropVLM: A Domain-Adapted Vision-Language Model for Open-Set Crop Analysis20260
  6. 21MAgSeg: Segmentation of Agricultural Landscapes in High-Resolution Satellite Imagery using Multimodal Large Language Models20260
  7. 22Benchmarking Vision-Language Models for Microscopic Plant Image Understanding20260
  8. 23You Are What You Prompt: Prompt Quality, Domain Shift, and Uncertainty in Agrifood Vision-Language Models20260
  9. 24Can Urban Blight Be Accessed with Vision-language Models: A Case Study in Detroit20260
  10. 25Fusing Perceptual Vision Experts with Multimodal Large Language Models for Explainable Plant Disease Diagnosis: From Benchmark Imagery to Real-World Robotic Field Validation20260
  11. 26BananaVLM: A Domain-Adapted Vision Language Model for Banana Crop Disease Diagnosis20260
  12. 27IchthyoNoma: Nomenclature and Context Sensitivity of Zero-Shot Biological Vision--Language Models for Bangladeshi Freshwater Fish Recognition20260
  13. 28Vision-language models know more about agriculture than they show and rubric-grounded verifications close the gap20260
  14. 29Can Edge-Deployable Vision-Language Models Identify Species?20260
  15. 30FungalZSL: Zero-Shot Fungal Classification with Image Captioning Using a Synthetic Data Approach20250
  16. 31A Vision-Language Foundation Model for Leaf Disease Identification20250
  17. 32CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text20250
  18. 33FishNet++: Analyzing the capabilities of Multimodal Large Language Models in marine biology20250
  19. 34Agro-Consensus: Semantic Self-Consistency in Vision-Language Models for Crop Disease Management in Developing Countries20250
  20. 35AgroCoT: A Chain-of-Thought Benchmark for Evaluating Reasoning in Vision-Language Models for Agriculture20250