Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Ortega, John E."'
Autor:
Miner, Jordan, Ortega, John E.
We propose a method to predict toxicity and other textual attributes through the use of natural language processing (NLP) techniques for two recent events: the Ukraine-Russia and Hamas-Israel conflicts. This article provides a basis for exploration i
Externí odkaz:
http://arxiv.org/abs/2410.06427
The typical workflow for a professional translator to translate a document from its source language (SL) to a target language (TL) is not always focused on what many language models in natural language processing (NLP) do - predict the next word in a
Externí odkaz:
http://arxiv.org/abs/2409.17943
Autor:
Yue, Richard, Ortega, John E.
Translation memories (TMs) are the backbone for professional translation tools called computer-aided translation (CAT) tools. In order to perform a translation using a CAT tool, a translator uses the TM to gather translations similar to the desired s
Externí odkaz:
http://arxiv.org/abs/2409.17939
Nollywood, based on the idea of Bollywood from India, is a series of outstanding movies that originate from Nigeria. Unfortunately, while the movies are in English, they are hard to understand for many native speakers due to the dialect of English th
Externí odkaz:
http://arxiv.org/abs/2407.02631
The application of self-supervision to speech representation learning has garnered significant interest in recent years, due to its scalability to large amounts of unlabeled data. However, much progress, both in terms of pre-training and downstream e
Externí odkaz:
http://arxiv.org/abs/2310.03639
Models based on bidirectional encoder representations from transformers (BERT) produce state of the art (SOTA) results on many natural language processing (NLP) tasks such as named entity recognition (NER), part-of-speech (POS) tagging etc. An intere
Externí odkaz:
http://arxiv.org/abs/2304.08649
Meeting the Needs of Low-Resource Languages: The Value of Automatic Alignments via Pretrained Models
Autor:
Ebrahimi, Abteen, McCarthy, Arya D., Oncevay, Arturo, Chiruzzo, Luis, Ortega, John E., Giménez-Lugo, Gustavo A., Coto-Solano, Rolando, Kann, Katharina
Large multilingual models have inspired a new class of word alignment methods, which work well for the model's pretraining languages. However, the languages most in need of automatic alignment are low-resource and, thus, not typically included in the
Externí odkaz:
http://arxiv.org/abs/2302.07912
Autor:
Singh, Ayush, Ortega, John E.
State-of-the-art pre-trained language models (PLMs) outperform other models when applied to the majority of language processing tasks. However, PLMs have been found to degrade in performance under distribution shift, a phenomenon that occurs when dat
Externí odkaz:
http://arxiv.org/abs/2212.02384
Autor:
Ortega, John E.
Publikováno v:
David C. Wyld et al. (Eds): CONEDU, CSITA, MLCL, ISPR, NATAP, ARIN - 2022, pp. 43-54, 2022. CS & IT
This work provides a survey of several networking cipher algorithms and proposes a method for integrating natural language processing (NLP) as a protective agent for them. Two main proposals are covered for the use of NLP in networking. First, NLP is
Externí odkaz:
http://arxiv.org/abs/2206.10924
Autor:
Ortega, John E.
La traducción asistida por ordenador (TAO) basada en memorias de traducción (MT) es ampliamente utilizado para ayudar a traductores profesionales. Una MT es un repositorio que contiene unidades de traducción (UT), esto es, pares de segmentos paral
Externí odkaz:
http://hdl.handle.net/10045/116315