# Agent Smith: Teaching Question Answering to Jill Watson

Source: [Agent Smith: Teaching Question Answering to Jill Watson](<https://www.sota2.com/research/paper/68fa6c2c1e209131cea328bc>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T00:05:48.516Z

Authors: Ashok Goel, Harshvardhan Sikka, Eric Gregori

Published: 2021-12-22T19:40:10.000Z

## Abstract

Building AI agents can be costly. Consider a question answering agent such as Jill Watson that automatically answers students' questions on the discussion forums of online classes based on their syllabi and other course materials. Training a Jill on the syllabus of a new online class can take a hundred hours or more. Machine teaching - interactive teaching of an AI agent using synthetic data sets - can reduce the training time because it combines the advantages of knowledge-based AI, machine learning using large data sets, and interactive human-in-loop training. We describe Agent Smith, an interactive machine teaching agent that reduces the time taken to train a Jill for a new online class by an order of magnitude.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2112.13677>)

[PDF](<https://arxiv.org/pdf/2112.13677.pdf>)