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Viewing 461-470 of 553 papers
  • Pros and Cons of Autonomous Weapons Systems

    Amitai Etzioni and Oren EtzioniMilitary Review2017 Autonomous weapons systems and military robots are progressing from science fiction movies to designers' drawing boards, to engineering laboratories, and to the battlefield. These machines have prompted a debate among military planners, roboticists, and… more
  • QSAnglyzer: Visual Analytics for Prismatic Analysis of Question Answering System Evaluations

    Nan-Chen Chen and Been KimVAST2017 Developing sophisticated artificial intelligence (AI) systems requires AI researchers to experiment with different designs and analyze results from evaluations (we refer this task as evaluation analysis). In this paper, we tackle the challenges of evaluation… more
  • Query-Reduction Networks for Question Answering

    Minjoon Seo, Sewon Min, Ali Farhadi, Hannaneh HajishirziICLR2017 In this paper, we study the problem of question answering when reasoning over multiple facts is required. We propose Query-Reduction Network (QRN), a variant of Recurrent Neural Network (RNN) that effectively handles both short-term (local) and long-term… more
  • See the Glass Half Full: Reasoning about Liquid Containers, their Volume and Content

    Roozbeh Mottaghi, Connor Schenck, Dieter Fox, Ali FarhadiICCV2017 Humans have rich understanding of liquid containers and their contents; for example, we can effortlessly pour water from a pitcher to a cup. Doing so requires estimating the volume of the cup, approximating the amount of water in the pitcher, and predicting… more
  • Should Artificial Intelligence Be Regulated?

    Amitai Etzioni and Oren EtzioniIssues in Science and Technology2017 New technologies often spur public anxiety, but the intensity of concern about the implications of advances in artificial intelligence (AI) is particularly noteworthy. Several respected scholars and technology leaders warn that AI is on the path to turning… more
  • Target-driven visual navigation in indoor scenes using deep reinforcement learning

    Yuke Zhu, Roozbeh Mottaghi, Eric Kolve, Joseph Lim, Abhinav Gupta, Fei-Fei Li, and Ali FarhadiICRA2017 Two less addressed issues of deep reinforcement learning are (1) lack of generalization capability to new goals, and (2) data inefficiency, i.e., the model requires several (and often costly) episodes of trial and error to converge, which makes it impractical… more
  • 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 HammondCoNLL2017 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… more
  • 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 PowerSemEval2017 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… more
  • 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. SmithCoNLL2017 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… more
  • Visual Semantic Planning using Deep Successor Representations

    Yuke Zhu, Daniel Gordon, Eric Kolve, Dieter Fox, Li Fei-Fei, Abhinav Gupta, Roozbeh Mottaghi, Ali FarhadiICCV2017 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… more
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