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Finding Deceptive Opinion Spam by Any Stretch of the Imagination
Consumers increasingly rate, review and research products online (Jansen, 2010; Litvin et al., 2008). Consequently, websites containing consumer reviews are becoming targets of opinion spam. WhileExpand
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Neural Motifs: Scene Graph Parsing with Global Context
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 newExpand
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The Curious Case of Neural Text Degeneration
Despite considerable advancements with deep neural language models, the enigma of neural text degeneration persists when these models are tested as text generators. The counter-intuitive empiricalExpand
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QuAC : Question Answering in Context
We present QuAC, a dataset for Question Answering in Context that contains 14K information-seeking QA dialogs (100K questions in total). The dialogs involve two crowd workers: (1) a student who posesExpand
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Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
Sequence-to-sequence models have shown strong performance across a broad range of applications. However, their application to parsing and generating text usingAbstract Meaning Representation (AMR)hasExpand
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OpinionFinder: A System for Subjectivity Analysis
OpinionFinder is a system that performs subjectivity analysis, automatically identifying when opinions, sentiments, speculations, and other private states are present in text. Specifically,Expand
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SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference
Given a partial description like "she opened the hood of the car," humans can reason about the situation and anticipate what might come next ("then, she examined the engine"). In this paper, weExpand
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Syntactic Stylometry for Deception Detection
Most previous studies in computerized deception detection have relied only on shallow lexico-syntactic patterns. This paper investigates syntactic stylometry for deception detection, adding aExpand
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ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning
We present ATOMIC, an atlas of everyday commonsense reasoning, organized through 877k textual descriptions of inferential knowledge. Compared to existing resources that center around taxonomicExpand
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Baby talk: Understanding and generating simple image descriptions
We posit that visually descriptive language offers computer vision researchers both information about the world, and information about how people describe the world. The potential benefit from thisExpand
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