Výsledky vyhledávání - "Hasan, Rakebul"

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FsPONER: Few-shot Prompt Optimization for Named Entity Recognition in Domain-specific Scenarios

Autor: Tang, Yongjian, Hasan, Rakebul, Runkler, Thomas

Large Language Models (LLMs) have provided a new pathway for Named Entity Recognition (NER) tasks. Compared with fine-tuning, LLM-powered prompting methods avoid the need for training, conserve substantial computational resources, and rely on minimal

Externí odkaz: http://arxiv.org/abs/2407.08035

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Named Entity Recognition in Industrial Tables using Tabular Language Models

Autor: Koleva, Aneta, Ringsquandl, Martin, Buckley, Mark, Hasan, Rakebul, Tresp, Volker

Specialized transformer-based models for encoding tabular data have gained interest in academia. Although tabular data is omnipresent in industry, applications of table transformers are still missing. In this paper, we study how these models can be a

Externí odkaz: http://arxiv.org/abs/2209.14812

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Dissertation/ Thesis

Prédire les performances des requêtes et expliquer les résultats pour assister la consommation de données liées

Autor: Hasan, Rakebul

Prédire les performances des requêtes et expliquer les résultats pour assister la consommation de données liées. Notre objectif est d'aider les utilisateurs à comprendre les performances d'interrogation SPARQL, les résultats de la requête, et

Externí odkaz: http://www.theses.fr/2014NICE4082/document

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Predicting query performance and explaining results to assist Linked Data consumption

Autor: Hasan, Rakebul

Publikováno v: Other [cs.OH]. Université Nice Sophia Antipolis, 2014. English. ⟨NNT : 2014NICE4082⟩

Our goal is to assist users in understanding SPARQL query performance, query results, and derivations on Linked Data. To help users in understanding query performance, we provide query performance predictions based on the query execution history. We

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::f0d63ab6a7876807385c0db3e22733bb
https://tel.archives-ouvertes.fr/tel-01127124/document

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