Explanatory and actionable debugging for machine learning: A tableQA demonstration

Minseok Cho, Gyeongbok Lee, Seung Won Hwang

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    Question answering from tables (TableQA) extracting answers from tables from the question given in natural language, has been actively studied. Existing models have been trained and evaluated mostly with respect to answer accuracy using public benchmark datasets such as WikiSQL. The goal of this demonstration is to show a debugging tool for such models, explaining answers to humans, known as explanatory debugging. Our key distinction is making it “actionable" to allow users to directly correct models upon explanation. Specifically, our tool surfaces annotation and models errors for users to correct, and provides actionable insights.

    Original languageEnglish
    Title of host publicationSIGIR 2019 - Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval
    PublisherAssociation for Computing Machinery, Inc
    Pages1333-1336
    Number of pages4
    ISBN (Electronic)9781450361729
    DOIs
    Publication statusPublished - 2019 Jul 18
    Event42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019 - Paris, France
    Duration: 2019 Jul 212019 Jul 25

    Publication series

    NameSIGIR 2019 - Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

    Conference

    Conference42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019
    Country/TerritoryFrance
    CityParis
    Period19/7/2119/7/25

    All Science Journal Classification (ASJC) codes

    • Information Systems
    • Applied Mathematics
    • Software

    Fingerprint

    Dive into the research topics of 'Explanatory and actionable debugging for machine learning: A tableQA demonstration'. Together they form a unique fingerprint.

    Cite this