Papers

Learn more about AI2's Lasting Impact Award
Viewing 801-810 of 974 papers
  • Citation Count Analysis for Papers with Preprints

    Sergey Feldman, Kyle Lo, Waleed AmmarArXiv2018 We explore the degree to which papers prepublished on arXiv garner more citations, in an attempt to paint a sharper picture of fairness issues related to prepublishing. A paper’s citation count is estimated using a negative-binomial generalized linear model…
  • Construction of the Literature Graph in Semantic Scholar

    Waleed Ammar, Dirk Groeneveld, Chandra Bhagavatula, Iz Beltagy, Miles Crawford, Doug Downey, Jason Dunkelberger, Ahmed Elgohary, Sergey Feldman, Vu Ha, Rodney Kinney, Sebastian Kohlmeier, Kyle Lo, Tyler Murray, Hsu-Han Ooi, Matthew E. Peters, et al.NAACL-HLT2018 We describe a deployed scalable system for organizing published scientific literature into a heterogeneous graph to facilitate algorithmic manipulation and discovery. The resulting literature graph consists of more than 280M nodes, representing papers…
  • Actor and Observer: Joint Modeling of First and Third-Person Videos

    Gunnar Sigurdsson, Cordelia Schmid, Ali Farhadi, Abhinav Gupta, Karteek AlahariCVPR2018 Several theories in cognitive neuroscience suggest that when people interact with the world, or simulate interactions, they do so from a first-person egocentric perspective, and seamlessly transfer knowledge between third-person (observer) and first-person…
  • Adversarial Training for Textual Entailment with Knowledge-Guided Examples

    Tushar Khot, Ashish Sabharwal and Dongyeop KangACL2018 We consider the problem of learning textual entailment models with limited supervision (5K-10K training examples), and present two complementary approaches for it. First, we propose knowledge-guided adversarial example generators for incorporating large…
  • AllenNLP: A Deep Semantic Natural Language Processing Platform

    Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson Liu, Matthew Peters, Michael Schmitz, Luke ZettlemoyerACL • NLP OSS Workshop2018 This paper describes AllenNLP, a platform for research on deep learning methods in natural language understanding. AllenNLP is designed to support researchers who want to build novel language understanding models quickly and easily. It is built on top of…
  • Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering

    Aishwarya Agrawal, Dhruv Batra, Devi Parikh, Aniruddha KembhaviCVPR2018 A number of studies have found that today’s Visual Question Answering (VQA) models are heavily driven by superficial correlations in the training data and lack sufficient image grounding. To encourage development of models geared towards the latter, we…
  • ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation

    Sachin Mehta, Mohammad Rastegari, Anat Caspi, Linda Shapiro, and Hannaneh HajishirziECCV2018 We introduce a fast and efficient convolutional neural network, ESPNet, for semantic segmentation of high resolution images under resource constraints. ESPNet is based on a new convolutional module, efficient spatial pyramid (ESP), which is efficient in terms…
  • Event2Mind: Commonsense Inference on Events, Intents, and Reactions

    Maarten Sap, Hannah Rashkin, Emily Allaway, Noah A. Smith and Yejin ChoiACL2018 We investigate a new commonsense inference task: given an event described in a short free-form text (“X drinks coffee in the morning”), a system reasons about the likely intents (“X wants to stay awake”) and reactions (“X feels alert”) of the event’s…
  • Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples

    Vidur Joshi, Matthew Peters, and Mark HopkinsACL2018 We revisit domain adaptation for parsers in the neural era. First we show that recent advances in word representations greatly diminish the need for domain adaptation when the target domain is syntactically similar to the source domain. As evidence, we train…
  • Imagine This! Scripts to Compositions to Videos

    Tanmay Gupta, Dustin Schwenk, Ali Farhadi, Derek Hoiem, and Aniruddha KembhaviECCV2018 Imagining a scene described in natural language with realistic layout and appearance of entities is the ultimate test of spatial, visual, and semantic world knowledge. Towards this goal, we present the Composition, Retrieval and Fusion Network (Craft), a…