Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Rei, Ricardo"'
Autor:
Treviso, Marcos, Guerreiro, Nuno M., Agrawal, Sweta, Rei, Ricardo, Pombal, José, Vaz, Tania, Wu, Helena, Silva, Beatriz, van Stigt, Daan, Martins, André F. T.
While machine translation (MT) systems are achieving increasingly strong performance on benchmarks, they often produce translations with errors and anomalies. Understanding these errors can potentially help improve the translation quality and user ex
Externí odkaz:
http://arxiv.org/abs/2406.19482
Autor:
Faria, Gonçalo R. A., Agrawal, Sweta, Farinhas, António, Rei, Ricardo, de Souza, José G. C., Martins, André F. T.
An important challenge in machine translation (MT) is to generate high-quality and diverse translations. Prior work has shown that the estimated likelihood from the MT model correlates poorly with translation quality. In contrast, quality evaluation
Externí odkaz:
http://arxiv.org/abs/2406.00049
Automatic metrics for evaluating translation quality are typically validated by measuring how well they correlate with human assessments. However, correlation methods tend to capture only the ability of metrics to differentiate between good and bad s
Externí odkaz:
http://arxiv.org/abs/2405.18348
Despite the recent success of automatic metrics for assessing translation quality, their application in evaluating the quality of machine-translated chats has been limited. Unlike more structured texts like news, chat conversations are often unstruct
Externí odkaz:
http://arxiv.org/abs/2403.08314
Autor:
Alves, Duarte M., Pombal, José, Guerreiro, Nuno M., Martins, Pedro H., Alves, João, Farajian, Amin, Peters, Ben, Rei, Ricardo, Fernandes, Patrick, Agrawal, Sweta, Colombo, Pierre, de Souza, José G. C., Martins, André F. T.
While general-purpose large language models (LLMs) demonstrate proficiency on multiple tasks within the domain of translation, approaches based on open LLMs are competitive only when specializing on a single task. In this paper, we propose a recipe f
Externí odkaz:
http://arxiv.org/abs/2402.17733
Autor:
Faysse, Manuel, Fernandes, Patrick, Guerreiro, Nuno M., Loison, António, Alves, Duarte M., Corro, Caio, Boizard, Nicolas, Alves, João, Rei, Ricardo, Martins, Pedro H., Casademunt, Antoni Bigata, Yvon, François, Martins, André F. T., Viaud, Gautier, Hudelot, Céline, Colombo, Pierre
We introduce CroissantLLM, a 1.3B language model pretrained on a set of 3T English and French tokens, to bring to the research and industrial community a high-performance, fully open-sourced bilingual model that runs swiftly on consumer-grade local h
Externí odkaz:
http://arxiv.org/abs/2402.00786
Autor:
Wang, Jiayi, Adelani, David Ifeoluwa, Agrawal, Sweta, Masiak, Marek, Rei, Ricardo, Briakou, Eleftheria, Carpuat, Marine, He, Xuanli, Bourhim, Sofia, Bukula, Andiswa, Mohamed, Muhidin, Olatoye, Temitayo, Adewumi, Tosin, Mokayed, Hamam, Mwase, Christine, Kimotho, Wangui, Yuehgoh, Foutse, Aremu, Anuoluwapo, Ojo, Jessica, Muhammad, Shamsuddeen Hassan, Osei, Salomey, Omotayo, Abdul-Hakeem, Chukwuneke, Chiamaka, Ogayo, Perez, Hourrane, Oumaima, Anigri, Salma El, Ndolela, Lolwethu, Mangwana, Thabiso, Mohamed, Shafie Abdi, Hassan, Ayinde, Awoyomi, Oluwabusayo Olufunke, Alkhaled, Lama, Al-Azzawi, Sana, Etori, Naome A., Ochieng, Millicent, Siro, Clemencia, Njoroge, Samuel, Muchiri, Eric, Kimotho, Wangari, Momo, Lyse Naomi Wamba, Abolade, Daud, Ajao, Simbiat, Shode, Iyanuoluwa, Macharm, Ricky, Iro, Ruqayya Nasir, Abdullahi, Saheed S., Moore, Stephen E., Opoku, Bernard, Akinjobi, Zainab, Afolabi, Abeeb, Obiefuna, Nnaemeka, Ogbu, Onyekachi Raphael, Brian, Sam, Otiende, Verrah Akinyi, Mbonu, Chinedu Emmanuel, Sari, Sakayo Toadoum, Lu, Yao, Stenetorp, Pontus
Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measuring this progress remains challenging, since evaluation is often performed on n-gram matching metrics such as
Externí odkaz:
http://arxiv.org/abs/2311.09828
Autor:
Alves, Duarte M., Guerreiro, Nuno M., Alves, João, Pombal, José, Rei, Ricardo, de Souza, José G. C., Colombo, Pierre, Martins, André F. T.
Large language models (LLMs) are a promising avenue for machine translation (MT). However, current LLM-based MT systems are brittle: their effectiveness highly depends on the choice of few-shot examples and they often require extra post-processing du
Externí odkaz:
http://arxiv.org/abs/2310.13448
Autor:
Guerreiro, Nuno M., Rei, Ricardo, van Stigt, Daan, Coheur, Luisa, Colombo, Pierre, Martins, André F. T.
Widely used learned metrics for machine translation evaluation, such as COMET and BLEURT, estimate the quality of a translation hypothesis by providing a single sentence-level score. As such, they offer little insight into translation errors (e.g., w
Externí odkaz:
http://arxiv.org/abs/2310.10482
Autor:
Rei, Ricardo, Guerreiro, Nuno M., Pombal, José, van Stigt, Daan, Treviso, Marcos, Coheur, Luisa, de Souza, José G. C., Martins, André F. T.
We present the joint contribution of Unbabel and Instituto Superior T\'ecnico to the WMT 2023 Shared Task on Quality Estimation (QE). Our team participated on all tasks: sentence- and word-level quality prediction (task 1) and fine-grained error span
Externí odkaz:
http://arxiv.org/abs/2309.11925