Agent Smith: Teaching Question Answering to Jill Watson
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Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 8 of its 17 references that are in the map. First posted on arXiv 22 Dec 2021.
Builds on
8 of 17 references.
References · 8
- 2019EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Taskscited by 807
- 2021A Survey of Data Augmentation Approaches for NLPcited by 409
- 2020Logic-Guided Data Augmentation and Regularization for Consistent Question Answeringcited by 78
- 2018An Overview of Machine Teachingcited by 63
- 2017Iterative Machine Teachingcited by 41
- 2019XLDA: Cross-Lingual Data Augmentation for Natural Language Inference and Question Answeringcited by 35
- 2020AI-Powered Learning: Making Education Accessible, Affordable, and Achievablecited by 9
- 2018A Survey Investigating Usage of Virtual Personal Assistantscited by 1
Built on by
Citing papers per year: 2022: 2; 2023: 2.
4 papers.
- 2023AI-TA: Towards an Intelligent Question-Answer Teaching Assistant using Open-Source LLMscited by 22
- 2023LittleMu: Deploying an Online Virtual Teaching Assistant via Heterogeneous Sources Integration and Chain of Teach Promptscited by 9
- 2022A Framework for Interactive Knowledge-Aided Machine Teachingcited by 3
- 2022Explanation as Question Answering based on a Task Model of the Agent's Designcited by 2
- 2023AI-TA: Towards an Intelligent Question-Answer Teaching Assistant using Open-Source LLMs5 Nov 2023
- 2023LittleMu: Deploying an Online Virtual Teaching Assistant via Heterogeneous Sources Integration and Chain of Teach Prompts11 Aug 2023
- 2022Explanation as Question Answering based on a Task Model of the Agent's Design8 Jun 2022
- 2022A Framework for Interactive Knowledge-Aided Machine Teaching21 Apr 2022