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Tell Me Why: Using Question Answering as Distant Supervision for Answer Justification
Rebecca Sharp, Mihai Surdeanu, Peter Jansen, Marco A. Valenzuela-Escárcega, Peter Clark, and Michael HammondCoNLL • 2017 For many applications of question answering (QA), being able to explain why a given model chose an answer is critical. However, the lack of labeled data for answer justifications makes learning this difficult and expensive. Here we propose an approach that…The AI2 system at SemEval-2017 Task 10 (ScienceIE): semi-supervised end-to-end entity and relation extraction
Waleed Ammar, Matthew E. Peters, Chandra Bhagavatula, and Russell PowerSemEval • 2017 This paper describes our submission for the ScienceIE shared task (SemEval-2017 Task 10) on entity and relation extraction from scientific papers. Our model is based on the end-to-end relation extraction model of Miwa and Bansal (2016) with several…The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task
Roy Schwartz, Maarten Sap, Ioannis Konstas, Leila Zilles, Yejin Choi, Noah A. SmithCoNLL • 2017 A writer’s style depends not just on personal traits but also on her intent and mental state. In this paper, we show how variants of the same writing task can lead to measurable differences in writing style. We present a case study based on the story cloze…Visual Semantic Planning using Deep Successor Representations
Yuke Zhu, Daniel Gordon, Eric Kolve, Dieter Fox, Li Fei-Fei, Abhinav Gupta, Roozbeh Mottaghi, Ali FarhadiICCV • 2017 A crucial capability of real-world intelligent agents is their ability to plan a sequence of actions to achieve their goals in the visual world. In this work, we address the problem of visual semantic planning: the task of predicting a sequence of actions…YOLO9000: Better, Faster, Stronger
Joseph Redmon, Ali FarhadiCVPR • 2017 We introduce YOLO9000, a state-of-the-art, real-time object detection system that can detect over 9000 object categories. First we propose various improvements to the YOLO detection method, both novel and drawn from prior work. The improved model, YOLOv2, is…Verb Physics: Relative Physical Knowledge of Actions and Objects
Maxwell Forbes, Yejin ChoiACL • 2017 Learning commonsense knowledge from natural language text is nontrivial due to reporting bias: people rarely state the obvious, e.g., “My house is bigger than me.” However, while rarely stated explicitly, this trivial everyday knowledge does influence the way…Detecting English Writing Styles For Non Native Speakers
Yanging Chen, Rami Al-Rfou, Yejin ChoiarXiv • 2017 This paper presents the first attempt, up to our knowledge, to classify English writing styles on this scale with the challenge of classifying day to day language written by writers with different backgrounds covering various areas of topics.The paper…Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge
Matt Gardner and Jayant KrishnamurthyAAAI • 2017 Traditional semantic parsers map language onto compositional, executable queries in a fixed schema. This map- ping allows them to effectively leverage the information con- tained in large, formal knowledge bases (KBs, e.g., Freebase) to answer questions, but…Probabilistic Neural Programs
Kenton W. Murray and Jayant KrishnamurthyNIPS • NAMPI Workshop • 2016 We present probabilistic neural programs, a framework for program induction that permits flexible specification of both a computational model and inference algorithm while simultaneously enabling the use of deep neural networks. Probabilistic neural programs…Designing AI Systems that Obey Our Laws and Values
Amitai Etzioni and Oren EtzioniCACM • 2016 Operational AI systems (for example, self-driving cars) need to obey both the law of the land and our values. We propose AI oversight systems ("AI Guardians") as an approach to addressing this challenge, and to respond to the potential risks associated with…