Papers

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Viewing 831-840 of 988 papers
  • Ultra-Fine Entity Typing

    Eunsol Choi, Omer Levy, Yejin Choi and Luke ZettlemoyerACL2018 We introduce a new entity typing task: given a sentence with an entity mention, the goal is to predict a set of free-form phrases (e.g. skyscraper, songwriter, or criminal) that describe appropriate types for the target entity. This formulation allows us to…
  • A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications

    Dongyeop Kang, Waleed Ammar, Bhavana Dalvi Mishra, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard Hovy, Roy SchwartzNAACL-HLT2018 Peer reviewing is a central component in the scientific publishing process. We present the first public dataset of scientific peer reviews available for research pur- poses (PeerRead v1), providing an opportunity to study this important artifact. The dataset…
  • Annotation Artifacts in Natural Language Inference Data

    Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Sam Bowman and Noah A. SmithNAACL2018 Large-scale datasets for natural language inference are created by presenting crowd workers with a sentence (premise), and asking them to generate three new sentences (hypotheses) that it entails, contradicts, or is logically neutral with respect to. We show…
  • Content-Based Citation Recommendation

    Chandra Bhagavatula, Sergey Feldman, Russell Power, Waleed AmmarNAACL-HLT2018 We present a content-based method for recommending citations in an academic paper draft. We embed a given query document into a vector space, then use its nearest neighbors as candidates, and rerank the candidates using a discriminative model trained to…
  • Deep Communicating Agents For Abstractive Summarization

    Asli Celikyilmaz, Antoine Bosselut, Xiaodong He and Yejin ChoiNAACL2018 We present deep communicating agents in an encoder-decoder architecture to address the challenges of representing a long document for abstractive summarization. With deep communicating agents, the task of encoding a long text is divided across multiple…
  • Deep Contextualized Word Representations

    Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, Luke ZettlemoyerNAACL2018 We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e.g., syntax and semantics), and (2) how these uses vary across linguistic contexts (i.e., to model polysemy). Our word vectors are…
  • Discourse-Aware Neural Rewards For Coherent Text Generation

    Antoine Bosselut, Asli Celikyilmaz, Xiaodong He, Jianfeng Gao, Po-Sen Huang and Yejin ChoiNAACL2018 In this paper, we investigate the use of discourse-aware rewards with reinforcement learning to guide a model to generate long, coherent text. In particular, we propose to learn neural rewards to model cross-sentence ordering as a means to approximate desired…
  • Extracting Scientific Figures with Distantly Supervised Neural Networks

    Noah Siegel, Nicholas Lourie, Russell Power and Waleed AmmarJCDL2018 Non-textual components such as charts, diagrams and tables provide key information in many scientific documents, but the lack of large labeled datasets has impeded the development of data-driven methods for scientific figure extraction. In this paper, we…
  • Natural Language to Structured Query Generation via Meta-Learning

    Po-Sen Huang, Chenglong Wang, Rishabh Singh, Wen-tau Yih, Xiaodong HeNAACL2018 In conventional supervised training, a model is trained to fit all the training examples. However, having a monolithic model may not always be the best strategy, as examples could vary widely. In this work, we explore a different learning protocol that treats…
  • Neural Motifs: Scene Graph Parsing with Global Context

    Rowan Zellers, Mark Yatskar, Sam Thomson, Yejin ChoiCVPR2018 We investigate the problem of producing structured graph representations of visual scenes. Our work analyzes the role of motifs: regularly appearing substructures in scene graphs. We present new quantitative insights on such repeated structures in the Visual…