Zobrazeno 1 - 10
of 396
pro vyhledávání: '"Jorge, Alípio"'
Publikováno v:
Progress in Artificial Intelligence. EPIA 2023. Lecture Notes in Computer Science(), vol 14115. Springer, Cham
Event extraction is an Information Retrieval task that commonly consists of identifying the central word for the event (trigger) and the event's arguments. This task has been extensively studied for English but lags behind for Portuguese, partly due
Externí odkaz:
http://arxiv.org/abs/2408.16932
Publikováno v:
SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (2024)
Event extraction is an NLP task that commonly involves identifying the central word (trigger) for an event and its associated arguments in text. ACE-2005 is widely recognised as the standard corpus in this field. While other corpora, like PropBank, p
Externí odkaz:
http://arxiv.org/abs/2408.16928
Temporal expression identification is crucial for understanding texts written in natural language. Although highly effective systems such as HeidelTime exist, their limited runtime performance hampers adoption in large-scale applications and producti
Externí odkaz:
http://arxiv.org/abs/2403.16804
Publikováno v:
PROPOR 2024
The recent advances in natural language processing (NLP) are linked to training processes that require vast amounts of corpora. Access to this data is commonly not a trivial process due to resource dispersion and the need to maintain these infrastruc
Externí odkaz:
http://arxiv.org/abs/2401.15400
Publikováno v:
Advances in Information Retrieval. ECIR 2024. Lecture Notes in Computer Science, vol 14612. Springer, Cham
The capabilities of the most recent language models have increased the interest in integrating them into real-world applications. However, the fact that these models generate plausible, yet incorrect text poses a constraint when considering their use
Externí odkaz:
http://arxiv.org/abs/2401.01825
The importance of systems that can extract structured information from textual data becomes increasingly pronounced given the ever-increasing volume of text produced on a daily basis. Having a system that can effectively extract such information in a
Externí odkaz:
http://arxiv.org/abs/2311.14583
Textual health records of cancer patients are usually protracted and highly unstructured, making it very time-consuming for health professionals to get a complete overview of the patient's therapeutic course. As such limitations can lead to suboptima
Externí odkaz:
http://arxiv.org/abs/2304.08999
Temporal information extraction (TIE) has attracted a great deal of interest over the last two decades, leading to the development of a significant number of datasets. Despite its benefits, having access to a large volume of corpora makes it difficul
Externí odkaz:
http://arxiv.org/abs/2301.04643
Autor:
Loureiro, Daniel, Jorge, Alípio Mário
Progress on commonsense reasoning is usually measured from performance improvements on Question Answering tasks designed to require commonsense knowledge. However, fine-tuning large Language Models (LMs) on these specific tasks does not directly eval
Externí odkaz:
http://arxiv.org/abs/2210.06376