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Viewing 7 papers from 2015 in PRIOR
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    • ICCV 2015
      Hamid Izadinia, Fereshteh Sadeghi, Santosh Divvala, Hanna Hajishirzi, Yejin Choi, and Ali Farhadi
      We introduce Segment-Phrase Table (SPT), a large collection of bijective associations between textual phrases and their corresponding segmentations. Leveraging recent progress in object recognition and natural language semantics, we show how we can successfully build a highquality segment-phrase…  (More)
    • EMNLP 2015
      Minjoon Seo, Hannaneh Hajishirzi, Ali Farhadi, Oren Etzioni, and Clint Malcolm
      This paper introduces GeoS, the first automated system to solve unaltered SAT geometry questions by combining text understanding and diagram interpretation. We model the problem of understanding geometry questions as submodular optimization, and identify a formal problem description likely to be…  (More)
    • AAAI • Workshop on Scholarly Big Data 2015
      Christopher Clark and Santosh Divvala
      Identifying and extracting figures and tables along with their captions from scholarly articles is important both as a way of providing tools for article summarization, and as part of larger systems that seek to gain deeper, semantic understanding of these articles. While many "off-the-shelf" tools…  (More)
    • CVPR 2015
      Fereshteh Sadeghi, Santosh Divvala, and Ali Farhadi
      How can we know whether a statement about our world is valid. For example, given a relationship between a pair of entities e.g., 'eat(horse, hay)', how can we know whether this relationship is true or false in general. Gathering such knowledge about entities and their relationships is one of the…  (More)
    • NIPS 2015
      Fereshteh Sadeghi, C. Lawrence Zitnick, and Ali Farhadi
      In this paper, we study the problem of answering visual analogy questions. These questions take the form of image A is to image B as image C is to what. Answering these questions entails discovering the mapping from image A to image B and then extending the mapping to image C and searching for the…  (More)
    • CVPR 2015
      Mohammad Rastegari, Hannaneh Hajishirzi, and Ali Farhadi
      In this paper we present a bottom-up method to instance level Multiple Instance Learning (MIL) that learns to discover positive instances with globally constrained reasoning about local pairwise similarities. We discover positive instances by optimizing for a ranking such that positive (top rank…  (More)
    • ICCV 2015
      Bilge Soran, Ali Farhadi, and Linda Shapiro
      We all have experienced forgetting habitual actions among our daily activities. For example, we probably have forgotten to turn the lights off before leaving a room or turn the stove off after cooking. In this paper, we propose a solution to the problem of issuing notifications on actions that may…  (More)