mlsanityData to 14 Oct 2026

Agribot: agriculture-specific question answer system

arXiv 2509.21535 ↗First posted 25 Sep 2025cs.CL cs.AI cs.LGcited by 1

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Abstract (arXiv)

India is an agro-based economy and proper information about agricultural practices is the key to optimal agricultural growth and output. In order to answer the queries of the farmer, we have build an agricultural chatbot based on the dataset from Kisan Call Center. This system is robust enough to answer queries related to weather, market rates, plant protection and government schemes. This system is available 24* 7, can be accessed through any electronic device and the information is delivered with the ease of understanding. The system is based on a sentence embedding model which gives an accuracy of 56%. After eliminating synonyms and incorporating entity extraction, the accuracy jumps to 86%. With such a system, farmers can progress towards easier information about farming related practices and hence a better agricultural output. The job of the Call Center workforce would be made easier and the hard work of various such workers can be redirected to a better goal.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 2 of its 12 references that are in the map. First posted on arXiv 25 Sep 2025.

Builds on

2 of 12 references.

References · 2

  1. 2018Know What You Don't Know: Unanswerable Questions for SQuADcited by 1,554
  2. 2014word2vec Parameter Learning Explainedcited by 53

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Citing papers per year: 2026: 1.

1 paper.