Zobrazeno 1 - 10
of 192
pro vyhledávání: '"Steven Schockaert"'
This book comprehensively studies fuzzy temporal and spatial information, starting from the basics on fuzzy set theory and temporal/spatial reasoning, the development of a new model to represent fuzzy temporal/spatial information, the study of effici
Publikováno v:
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::edadff4f4e32c8eb8550357e059395d7
https://doi.org/10.18653/v1/2022.semeval-1.38
https://doi.org/10.18653/v1/2022.semeval-1.38
Publikováno v:
6th Workshop on Representation Learning for NLP (RepL4NLP 2021)
One of the long-standing challenges in lexical semantics consists in learning representations of words which reflect their semantic properties. The remarkable success of word embeddings for this purpose suggests that high-quality representations can
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::532cfedd138a04a81b22d370aea2ca71
http://arxiv.org/abs/2106.07947
http://arxiv.org/abs/2106.07947
Publikováno v:
AAAI
Proceedings of the AAAI Conference on Artificial Intelligence
Proceedings of the AAAI Conference on Artificial Intelligence
The GloVe word embedding model relies on solving a global optimization problem, which can be reformulated as a maximum likelihood estimation problem. In this paper, we propose to generalize this approach to word embedding by considering parametrized
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e344d6a8e3abd07591628e20b2c28a70
https://doi.org/10.1609/aaai.v33i01.33016562
https://doi.org/10.1609/aaai.v33i01.33016562
Autor:
Steven Schockaert, Rafael Peñaloza
Publikováno v:
AI Communications. 35:45-45
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2391adef4a2977ae2fb32357f5ab54d1
https://doi.org/10.3233/aic-229002
https://doi.org/10.3233/aic-229002
Publikováno v:
30th International Joint Conference on Artificial Intelligence (IJCAI 2021)
IJCAI
IJCAI
Ontologies formalise how the concepts from a given domain are interrelated. Despite their clear potential as a backbone for explainable AI, existing ontologies tend to be highly incomplete, which acts as a significant barrier to their more widespread
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::551a87fcd150f2b4810484395e919c11
http://arxiv.org/abs/2105.04620
http://arxiv.org/abs/2105.04620
Publikováno v:
ICMR
ACM International Conference on Multimedia Retrieval (ACM ICMR 2021)
ACM International Conference on Multimedia Retrieval (ACM ICMR 2021)
Few-shot learning (FSL) is the task of learning to recognize previously unseen categories of images from a small number of training examples. This is a challenging task, as the available examples may not be enough to unambiguously determine which vis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3be22659d29424c1f9385738faa69050
Publikováno v:
ACL/IJCNLP (1)
59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)
59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)
Analogies play a central role in human commonsense reasoning. The ability to recognize analogies such as "eye is to seeing what ear is to hearing", sometimes referred to as analogical proportions, shape how we structure knowledge and understand langu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd5b3c17e8158f796e5505fedd2e11aa
Publikováno v:
ACL/IJCNLP (Findings)
Findings
Findings
Pre-trained language models such as ClinicalBERT have achieved impressive results on tasks such as medical Natural Language Inference. At first glance, this may suggest that these models are able to perform medical reasoning tasks, such as mapping sy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::909f95bef10b68260d6fac5deb984137
https://doi.org/10.18653/v1/2021.findings-acl.266
https://doi.org/10.18653/v1/2021.findings-acl.266