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This thesis concerns itself with variation in parallel linguistic data and how to model it for the purpose of machine translation. It also reflects the paradigm shift from phrase-based to neural machine translation in that it addresses the variation phenomena in both frameworks.
Machine transla...
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A Tale of Two Sequences: Interpretable and Linguistically-Informed Deep Learning for Natural Language Processing
Jasmijn Bastings
Deep Learning (DL) has swiftly taken over our field of NLP. It caused a shift from exploiting linguistic features and structures, such as POS-tags, dependency and co...
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This thesis presents investigations of the cognitive and neuronal processes that take part in the comprehension and production of scalar adjectives such as ‘large’, ‘long’, ‘loud’, ‘quiet’ and quantifiers such as ‘many’, ‘few’, ‘most’. The main topic of this thesis (Chapters 2-4 ) concerns the po...
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Linguistic Variation in Online Communities: A Computational Perspective
Marco Del Tredici
The same word can be used by different people to mean different things. The observed meaning variation is not random, but determined by the social characteristics of the speakers using it. In particular, a...
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This thesis investigates rhythm perception using computational modeling techniques and develops a set of tools and techniques for the definition and evaluation of probabilistic generative models of music perception. We argue that previously proposed computational models of rhythm perception insuf...
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According to the traditional picture in semantics, the meaning of a sentence is given by its truth conditions: they state what the world has to be like for the sentence to be true. This dissertation is about two phenomena that both require a refinement of this picture: indexicality and questions....
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This dissertation focuses on the study of inquisitive first order logic, a logical formalism encompassing questions in the presence of quantification, developed in order to employ questions in formal inferences and study their logical properties. In particular, we focus on developing tools and te...
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This dissertation advances the debate on how we have justified beliefs about non-actual possibilities. It evaluates imagination-based and similarity-based approaches to the epistemology of possibility, develops novel accounts of each of them, and examines the role of possibility-judgements in ph...
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This dissertation studies logical systems merging insights from logics of agency, counterfactuals, and norms. The aim is to develop tools to address three general questions related to a formal analysis of causal responsibily (i.e., responsibility for what happened, regardless of one's intentions...
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This dissertation bridges the theory of algorithmic randomness - a branch of computability theory - and the foundations of inductive learning. Algorithmic randomness provides a mathematical analysis of the notion of an individual object (such as a string of bytes representing a computer file or a...
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This dissertation explores the possibilities and impossibilities of securely delegating and distributing quantum computations. We construct explicit protocols for several quantum-cryptographic primitives (quantum message authentication, multi-party quantum computation, and verifiable quantum homo...