mlsanityData to 14 Oct 2026

Farmer.Chat: Scaling AI-Powered Agricultural Services for Smallholder Farmers

arXiv 2409.08916 ↗First posted 13 Sep 2024cs.ET cs.AI cs.HCcited by 13

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Abstract (arXiv)

Small and medium-sized agricultural holders face challenges like limited access to localized, timely information, impacting productivity and sustainability. Traditional extension services, which rely on in-person agents, struggle with scalability and timely delivery, especially in remote areas. We introduce FarmerChat, a generative AI-powered chatbot designed to address these issues. Leveraging Generative AI, FarmerChat offers personalized, reliable, and contextually relevant advice, overcoming limitations of previous chatbots in deterministic dialogue flows, language support, and unstructured data processing. Deployed in four countries, FarmerChat has engaged over 15,000 farmers and answered over 300,000 queries. This paper highlights how FarmerChat's innovative use of GenAI enhances agricultural service scalability and effectiveness. Our evaluation, combining quantitative analysis and qualitative insights, highlights FarmerChat's effectiveness in improving farming practices, enhancing trust, response quality, and user engagement.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 8 of its 78 references that are in the map. First posted on arXiv 13 Sep 2024.

Builds on

8 of 78 references.

References · 8

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2022Red Teaming Language Models with Language Modelscited by 1,026
  3. 2024A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Modelscited by 452
  4. 2023MEGA: Multilingual Evaluation of Generative AIcited by 293
  5. 2024RedAgent: Red Teaming Large Language Models with Context-aware Autonomous Language Agentcited by 44
  6. 2020Language Models as Few-Shot Learner for Task-Oriented Dialogue Systemscited by 41
  7. 2015A Survey of Available Corpora for Building Data-Driven Dialogue Systemscited by 33
  8. 2022Farmer-Bot: An Interactive Bot for Farmerscited by 2

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Citing papers per year: 2025: 4; 2026: 9.

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  1. 2025Building Benchmarks from the Ground Up: Community-Centered Evaluation of LLMs in Healthcare Chatbot Settingscited by 5
  2. 2025AgroAskAI: A Multi-Agentic AI Framework for Supporting Smallholder Farmers' Enquiries Globallycited by 2
  3. 2026Fine-Tuning and Evaluating Conversational AI for Agricultural Advisorycited by 2
  4. 2025The Hardness of Achieving Impact in AI for Social Impact Research: A Ground-Level View of Challenges & Opportunitiescited by 1
  5. 2025Leveraging Synthetic Data for Question Answering with Multilingual LLMs in the Agricultural Domaincited by 1
  6. 2026Multilinguality at the Edge: Developing Language Models for the Global Southcited by 1
  7. 2026KrishokChat: A Provenance-Traceable Multi-Task Bengali Agricultural Benchmark with Safety-Critical Chemical Advisorycited by 1
  8. 2026Kissan-Dost: Bridging the Last Mile in Smallholder Precision Agriculture with Conversational IoTcited by 0
  9. 2026CultivAgents: Cultivating Relationship-Centered Multi-Agent Systems for Personalized Gardeningcited by 0
  10. 2026Agri-SAGE: Simulation-Grounded Multi-Agent LLM for Context-Aware Agricultural Advisory Generationcited by 0
  11. 2026Where Does Retrieval Fail? Evaluating RAG Architectures for Agricultural Advisorycited by 0
  12. 2026Configurable Multi-Stage Vision Pipeline for Crop Disease and Pest Diagnosiscited by 0
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  1. 2026Tool-calling retrieval versus vector RAG for a small Greek--English knowledge base: accuracy and robustness to how users type Greekcited by 0