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Titlebook: Logic and Algorithms in Computational Linguistics 2021 (LACompLing2021); Roussanka Loukanova,Peter LeFanu Lumsdaine,Reinhar Book 2023 The

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發(fā)表于 2025-3-23 11:28:56 | 只看該作者
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發(fā)表于 2025-3-23 15:12:27 | 只看該作者
,Generalized Computable Models and?Montague Semantics,ral language sentences. For example, finite-order functionals play a crucial role in Montague intensional logic and formal semantics for natural languages. We discuss some computable models for the spaces of finite-order functionals based on the Ershov-Scott theory of domains and approximation space
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發(fā)表于 2025-3-23 20:47:50 | 只看該作者
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發(fā)表于 2025-3-24 00:41:09 | 只看該作者
,Decomposing Events into?GOLOG, by a verb can be decomposed into some complex expression which might or might not include one or more primitive predicates expressing acts or results of acts. I develop an account of event-semantic decomposition into GOLOG programs, a variety of the Situation Calculus. The result is an implemented
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發(fā)表于 2025-3-24 05:28:34 | 只看該作者
16#
發(fā)表于 2025-3-24 07:59:36 | 只看該作者
,White Roses, Red Backgrounds: Bringing Structured Representations to?Search,atural language processing. However, many of the NLP algorithms used in production systems fail for queries that require structured understanding of the query and document or that require reasoning. These issues arise because of the way information is stored in the search index and the need to retur
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發(fā)表于 2025-3-24 12:24:08 | 只看該作者
18#
發(fā)表于 2025-3-24 17:09:37 | 只看該作者
,Integrating Deep Neural Networks with?Dependent Type Semantics,develop a theory or system of natural language understanding that can perform complex inferences while being learnable. In this study, we propose a theory of language understanding that fuses neural language models and dependent type semantics (DTS), a proof-theoretic semantics of natural language b
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發(fā)表于 2025-3-24 20:32:57 | 只看該作者
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發(fā)表于 2025-3-25 02:03:36 | 只看該作者
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