Results 31 to 40 of about 368,749 (284)
Novelty Detection: A Perspective from Natural Language Processing
Computational Linguistics, 2022 The quest for new information is an inborn human trait and has always been quintessential for human survival and progress. Novelty drives curiosity, which in turn drives innovation.
Tirthankar Ghosal +4 more
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Recognising textual entailment with logical inference [PDF]
Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05, 2005 We use logical inference techniques for recognising textual entailment. As the performance of theorem proving turns out to be highly dependent on not readily available background knowledge, we incorporate model building, a technique borrowed from automated reasoning, and show that it is a useful robust method to approximate entailment.
Johan Bos, Katja Markert
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Engineering ProceedingsThis paper investigates the domain of Natural Language Inference (NLI), with an emphasis on Recognizing Textual Entailment (RTE). We utilize the Stanford Natural Language Inference (SNLI) dataset, a benchmark for RTE tasks, to examine the efficacy of ...
Franklin Quilumba +2 more
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BioASQ-QA: A manually curated corpus for Biomedical Question Answering
Scientific Data, 2023 The BioASQ question answering (QA) benchmark dataset contains questions in English, along with golden standard (reference) answers and related material.
Anastasia Krithara +3 more
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A semantic approach to recognizing textual entailment [PDF]
Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05, 2005 Exhaustive extraction of semantic information from text is one of the formidable goals of state-of-the-art NLP systems. In this paper, we take a step closer to this objective. We combine the semantic information provided by different resources and extract new semantic knowledge to improve the performance of a recognizing textual entailment system.
Marta Tatu, Dan I. Moldovan
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Optimizing textual entailment recognition using particle swarm optimization
, 2009 This paper introduces a new method to improve tree edit distance approach to textual entailment recognition, using particle swarm optimization. Currently, one of the main constraints of recognizing textual entailment using tree edit distance is to ...
Yashar Mehdad +3 more
core +1 more source
Transactions of the Association for Computational Linguistics, 2021 Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English.
Daniel Khashabi +24 more
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Inference rules for recognizing textual entailment [PDF]
Proceedings of the Eighth International Conference on Computational Semantics - IWCS-8 '09, 2009 In this paper, we explore the application of inference rules for recognizing textual entailment (RTE). We start with an automatically acquired collection and then propose methods to refine it and obtain more rules using a hand-crafted lexical resource.
Georgiana Dinu, Rui Wang 0005
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Loneliness is associated with adverse physical and mental health outcomes and remains understudied in children and adolescents undergoing cancer therapy. Pediatric oncology patients may be at increased risk due to medical isolation and disruption of social networks.
Charlotte N. Stahlfeld +5 more
wiley +1 more source
IEEE AccessNatural Language Inference (NLI) processes pairs of sentences to extract their semantic relations. NLI has been a hot research topic, integrated as a main component in other NLP applications, from morphological spelling correction tasks to higher-level ...
Khloud Al Jallad +2 more
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