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of 23
pro vyhledávání: '"Vougiouklis, Pavlos"'
We focus on Text-to-SQL semantic parsing from the perspective of Large Language Models. Motivated by challenges related to the size of commercial database schemata and the deployability of business intelligence solutions, we propose an approach that
Externí odkaz:
http://arxiv.org/abs/2407.03227
Autor:
Huang, Wenyu, Zhou, Guancheng, Lapata, Mirella, Vougiouklis, Pavlos, Montella, Sebastien, Pan, Jeff Z.
Although Large Language Models (LLMs) are effective in performing various NLP tasks, they still struggle to handle tasks that require extensive, real-world knowledge, especially when dealing with long-tail facts (facts related to long-tail entities).
Externí odkaz:
http://arxiv.org/abs/2405.06524
Identifying and understanding user intents is a pivotal task for E-Commerce. Despite its popularity, intent understanding has not been consistently defined or accurately benchmarked. In this paper, we focus on predicative user intents as "how a custo
Externí odkaz:
http://arxiv.org/abs/2402.14901
We present a system for knowledge graph population with Language Models, evaluated on the Knowledge Base Construction from Pre-trained Language Models (LM-KBC) challenge at ISWC 2022. Our system involves task-specific pre-training to improve LM repre
Externí odkaz:
http://arxiv.org/abs/2208.12539
Autor:
Vougiouklis, Pavlos
Most people need textual or visual interfaces in order to make sense of Semantic Web data. In this thesis, we investigate the problem of generating natural language summaries for structured data encoded as triples using neural networks. We propose an
Externí odkaz:
https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.766858
Autor:
Kaffee, Lucie-Aimée, Elsahar, Hady, Vougiouklis, Pavlos, Gravier, Christophe, Laforest, Frédérique, Hare, Jonathon, Simperl, Elena
While Wikipedia exists in 287 languages, its content is unevenly distributed among them. In this work, we investigate the generation of open domain Wikipedia summaries in underserved languages using structured data from Wikidata. To this end, we prop
Externí odkaz:
http://arxiv.org/abs/1803.07116
Autor:
Vougiouklis, Pavlos, Elsahar, Hady, Kaffee, Lucie-Aimée, Gravier, Christoph, Laforest, Frederique, Hare, Jonathon, Simperl, Elena
Most people do not interact with Semantic Web data directly. Unless they have the expertise to understand the underlying technology, they need textual or visual interfaces to help them make sense of it. We explore the problem of generating natural la
Externí odkaz:
http://arxiv.org/abs/1711.00155
Publikováno v:
In Patterns 13 November 2020 1(8)
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