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FOIL it! Find One mismatch between Image and Language caption.

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Comparatives, Quantifiers, Proportions: a Multi-Task Model for the Learning of Quantities from Vision., , and . NAACL-HLT, page 419-430. Association for Computational Linguistics, (2018)Some of Them Can be Guessed! Exploring the Effect of Linguistic Context in Predicting Quantifiers., , , and . ACL (2), page 114-119. Association for Computational Linguistics, (2018)FOIL it! Find One mismatch between Image and Language caption., , , , , , and . ACL (1), page 255-265. Association for Computational Linguistics, (2017)Building a Bagpipe with a Bag and a Pipe: Exploring Conceptual Combination in Vision., , and . VL@ACL, The Association for Computer Linguistics, (2016)The Wisdom of MaSSeS: Majority, Subjectivity, and Semantic Similarity in the Evaluation of VQA., , , , and . CoRR, (2018)Learning quantification from images: A structured neural architecture., , , and . Natural Language Engineering, 24 (3): 363-392 (2018)Can You See the (Linguistic) Difference? Exploring Mass/Count Distinction in Vision., , , , and . IWCS(2), The Association for Computer Linguistics, (2017)"Look, some Green Circles!": Learning to Quantify from Images., , , , , and . VL@ACL, The Association for Computer Linguistics, (2016)Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts., and . EMNLP/IJCNLP (1), page 2865-2876. Association for Computational Linguistics, (2019)Pay Attention to Those Sets! Learning Quantification from Images., , , , and . CoRR, (2017)