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Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input ...
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Latent Tree Learning with Differentiable Parsers: Shift-Reduce Parsing and Chart Parsing ...
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Visually Grounded and Textual Semantic Models Differentially Decode Brain Activity Associated with Concrete and Abstract Nouns ...
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Modelling metaphor with attribute-based semantics
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Bulat, L; Clark, Stephen; Shutova, Ekaterina. - : Association for Computational Linguistics, 2017. : Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2017
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Virtual Embodiment: A Scalable Long-Term Strategy for Artificial Intelligence Research ...
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Comparing Data Sources and Architectures for Deep Visual Representation Learning in Semantics ...
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Abstract:
Multi-modal distributional models learn grounded representations for improved performance in semantics. Deep visual representations, learned using convolutional neural networks, have been shown to achieve particularly high performance. In this study, we systematically compare deep visual representation learning techniques, experimenting with three well-known network architectures. In addition, we explore the various data sources that can be used for retrieving relevant images, showing that images from search engines perform as well as, or better than, those from manually crafted resources such as ImageNet. Furthermore, we explore the optimal number of images and the multi-lingual applicability of multi-modal semantics. We hope that these findings can serve as a guide for future research in the field. ... : Anita Verõ is supported by the Nuance Foundation Grant: Learning Type-Driven Distributed Representations of Language. Stephen Clark is supported by the ERC Starting Grant: DisCoTex (306920). ...
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URL: https://dx.doi.org/10.17863/cam.9060 https://www.repository.cam.ac.uk/handle/1810/263697
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Multi-Modal Representations for Improved Bilingual Lexicon Learning ...
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Multi-Modal Representations for Improved Bilingual Lexicon Learning
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Vulić, I; Kiela, D; Clark, Stephen. - : Association for Computational Linguistics, 2016. : http://acl2016.org/, 2016. : Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016
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Comparing Data Sources and Architectures for Deep Visual Representation Learning in Semantics
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Kiela, D; Vero, Anita; Clark, Stephen. - : Association for Computational Linguistics, 2016. : Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016
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RELPRON: A Relative Clause Evaluation Dataset for Compositional Distributional Semantics
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Vision and Feature Norms: Improving automatic feature norm learning through cross-modal maps
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Bulat, L; Kiela, D; Clark, Stephen. - : Association for Computational Linguistics, 2016. : http://www.aclweb.org/anthology/N/N16/, 2016. : Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016
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Expected F-Measure Training for Shift-Reduce Parsing with Recurrent Neural Networks
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Xu, W; Auli, M; Clark, Stephen. - : Association for Computational Linguistics, 2016. : Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016
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Using Sentence Plausibility to Learn the Semantics of Transitive Verbs ...
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The Frobenius anatomy of word meanings I: subject and object relative pronouns ...
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Participant Reference in Narrative Discourse: A Comparison of Three Methodologies
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Concrete Sentence Spaces for Compositional Distributional Models of Meaning ...
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