Zobrazeno 1 - 10
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pro vyhledávání: '"PONZETTO A"'
Autor:
Zhang, Leixin, Eger, Steffen, Cheng, Yinjie, Zhai, Weihe, Belouadi, Jonas, Leiter, Christoph, Ponzetto, Simone Paolo, Moafian, Fahimeh, Zhao, Zhixue
Multimodal large language models (LLMs) have demonstrated impressive capabilities in generating high-quality images from textual instructions. However, their performance in generating scientific images--a critical application for accelerating scienti
Externí odkaz:
http://arxiv.org/abs/2412.02368
Requirements Elicitation (RE) is a crucial activity especially in the early stages of software development. GUI prototyping has widely been adopted as one of the most effective RE techniques for user-facing software systems. However, GUI prototyping
Externí odkaz:
http://arxiv.org/abs/2409.16388
Autor:
Kolthoff, Kristian, Kretzer, Felix, Bartelt, Christian, Maedche, Alexander, Ponzetto, Simone Paolo
Interactive systems are omnipresent today and the need to create graphical user interfaces (GUIs) is just as ubiquitous. For the elicitation and validation of requirements, GUI prototyping is a well-known and effective technique, typically employed a
Externí odkaz:
http://arxiv.org/abs/2406.08120
Creating high-quality scientific figures can be time-consuming and challenging, even though sketching ideas on paper is relatively easy. Furthermore, recreating existing figures that are not stored in formats preserving semantic information is equall
Externí odkaz:
http://arxiv.org/abs/2405.15306
Extensive efforts in the past have been directed toward the development of summarization datasets. However, a predominant number of these resources have been (semi)-automatically generated, typically through web data crawling, resulting in subpar res
Externí odkaz:
http://arxiv.org/abs/2403.05303
Keywords, that is, content-relevant words in summaries play an important role in efficient information conveyance, making it critical to assess if system-generated summaries contain such informative words during evaluation. However, existing evaluati
Externí odkaz:
http://arxiv.org/abs/2403.05186
Large language models (LLMs) have recently revolutionized automated text understanding and generation. The performance of these models relies on the high number of parameters of the underlying neural architectures, which allows LLMs to memorize part
Externí odkaz:
http://arxiv.org/abs/2401.14931
Autor:
Sarracén, Gretel Liz De la Peña, Rosso, Paolo, Litschko, Robert, Glavaš, Goran, Ponzetto, Simone Paolo
Cross-lingual transfer learning from high-resource to medium and low-resource languages has shown encouraging results. However, the scarcity of resources in target languages remains a challenge. In this work, we resort to data augmentation and contin
Externí odkaz:
http://arxiv.org/abs/2311.02025
We present a cross-domain approach for automated measurement and context extraction based on pre-trained language models. We construct a multi-source, multi-domain corpus and train an end-to-end extraction pipeline. We then apply multi-source task-ad
Externí odkaz:
http://arxiv.org/abs/2308.02951
Autor:
Umberto Camellin, Massimo Camellin, Marcello Prantera, Roberta Di Pietro, Francesca Ponzetto, Pasquale Aragona
Publikováno v:
Indian Journal of Ophthalmology, Vol 72, Iss Suppl 5, Pp S831-S837 (2024)
Purpose: To estimate the pupil size (at the iris plane) under photopic (PPH) and scotopic (PS) conditions after phacoemulsification with intraocular lens (IOL) implantation. Methods: This retrospective observational cohort study included 190 virgin e
Externí odkaz:
https://doaj.org/article/c80e2f86571149a397b08dea13aae47b
