{"type":"ScholarlyArticle","title":"Technical, Hard and Explainable Question Answering (THE-QA)","authors":[{"name":"Shailaja Sampat","slug":"shailaja-sampat","given":"Shailaja","family":"Sampat","affiliation":"School of Computing, Informatics and Decision Systems Engineering , Arizona State University"}],"abstract":"The ability of an agent to rationally answer questions about a given task is the key measure of its intelligence. While we have obtained phenomenal performance over various language and vision tasks separately, 'Technical, Hard and Explainable Question Answering' (THE-QA) is a new challenging corpus which addresses them jointly. THE-QA is a question answering task involving diagram understanding and reading comprehension. We plan to establish benchmarks over this new corpus using deep learning models guided by knowledge representation methods. The proposed approach will envisage detailed semantic parsing of technical figures and text, which is robust against diverse formats. It will be aided by knowledge acquisition and reasoning module that categorizes different knowledge types, identify sources to acquire that knowledge and perform reasoning to answer the questions correctly. THE-QA data will present a strong challenge to the community for future research and  will bridge the gap between state-of-the-art Artificial Intelligence (AI) and 'Human-level' AI.","doi":"10.24963/ijcai.2019/916","url":"https://ijcai.org/proceedings/2019/916","pdf":"https://ijcai.org/proceedings/2019/0916.pdf","markdown":"https://ijcai.org/proceedings/2019/916.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/916","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":916,"pages":{"first":6454,"last":6455},"keywords":["Computer Vision: Language and Vision","Natural Language Processing: Question Answering","Natural Language Processing: Knowledge Extraction"],"videos":[],"references":[{"position":1,"raw":"[Aditya et al., 2015] Somak Aditya, Yezhou Yang, Chitta Baral, Cornelia Fermuller, and Yiannis Aloimonos. From images to sentences through scene description graphs. arXiv preprint arXiv:1511.03292, 2015.","title":"From images to sentences through scene description graphs","authors":"Somak Aditya, Yezhou Yang, Chitta Baral, Cornelia Fermuller, Yiannis Aloimonos","year":"2015","venue":null,"doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Baral et al., 2013] Chitta Baral, Juraj Dzifcak, Kanchan Kumbhare, and Nguyen H Vo. The nl2kr system. NLPAR, 2013, 2013.","title":"The nl2kr system","authors":"Chitta Baral, Juraj Dzifcak, Kanchan Kumbhare, H Nguyen, Vo","year":"2013","venue":"NLPAR","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Gelfond and Lifschitz, 1988] Michael Gelfond and Vladimir Lifschitz. The stable model semantics for logic programming. In Proceedings of JICSLP, pages 1070-1080. MIT Press, 1988.","title":"The stable model semantics for logic programming","authors":"Michael Gelfond, Vladimir Lifschitz","year":"1988","venue":"Proceedings of JICSLP","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Muggleton, 1991] Stephen Muggleton. Inductive logic pro- gramming. New generation computing, 8(4):295-318, 1991. [OECD, 2016] OECD. Pisa: Programme for international student assessment. 2016.","title":"Inductive logic programming","authors":"Stephen Muggleton","year":"1991","venue":"New generation computing","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}