Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Lupo, Lorenzo"'
Social scientists increasingly use demographically stratified social media data to study the attitudes, beliefs, and behavior of the general public. To facilitate such analyses, we construct, validate, and release publicly the representative DADIT da
Externí odkaz:
http://arxiv.org/abs/2403.05700
Recent advances in large language models (LLMs) like GPT-3.5 and GPT-4 promise automation with better results and less programming, opening up new opportunities for text analysis in political science. In this study, we evaluate LLMs on three original
Externí odkaz:
http://arxiv.org/abs/2311.11844
Context-aware translation can be achieved by processing a concatenation of consecutive sentences with the standard Transformer architecture. This paper investigates the intuitive idea of providing the model with explicit information about the positio
Externí odkaz:
http://arxiv.org/abs/2302.06459
A straightforward approach to context-aware neural machine translation consists in feeding the standard encoder-decoder architecture with a window of consecutive sentences, formed by the current sentence and a number of sentences from its context con
Externí odkaz:
http://arxiv.org/abs/2210.13388
Multi-encoder models are a broad family of context-aware neural machine translation systems that aim to improve translation quality by encoding document-level contextual information alongside the current sentence. The context encoding is undertaken b
Externí odkaz:
http://arxiv.org/abs/2103.17151
Autor:
BOSE, PAUL1 paul.bose@unibocconi.it, LUPO, LORENZO1 lorenzo.lupo2@unibocconi.it, HABIBI, MAHYAR1 mahyar.habibi@phd.unibocconi.it, HOVY, DIRK1 dirk.hovy@unibocconi.it, SCHWARZ, CARLO1 carlo.schwarz@unibocconi.it
Publikováno v:
AEA Papers & Proceedings. May2024, Vol. 114, p690-694. 5p.
Autor:
Veroux, Pierfrancesco, Giaquinta, Alessia, Perricone, Debora, Lupo, Lorenzo, Gentile, Flavia, Virgilio, Carla, Carbonaro, Anna, De Pasquale, Concetta, Veroux, Massimiliano
Publikováno v:
In Journal of Vascular and Interventional Radiology December 2013 24(12):1790-1797
Multi-encoder models are a broad family of context-aware Neural Machine Translation (NMT) systems that aim to improve translation quality by encoding document-level contextual information alongside the current sentence. The context encoding is undert
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::7f4dd349a8d9039b089cd3f74cbd941e
https://hal.archives-ouvertes.fr/hal-03455113
https://hal.archives-ouvertes.fr/hal-03455113
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.