Zobrazeno 1 - 10
of 6 024
pro vyhledávání: '"Haddow, A"'
Generic sentences express generalisations about the world without explicit quantification. Although generics are central to everyday communication, building a precise semantic framework has proven difficult, in part because speakers use generics to g
Externí odkaz:
http://arxiv.org/abs/2412.11318
Autor:
Ahmad, Ibrahim Said, Anastasopoulos, Antonios, Bojar, Ondřej, Borg, Claudia, Carpuat, Marine, Cattoni, Roldano, Cettolo, Mauro, Chen, William, Dong, Qianqian, Federico, Marcello, Haddow, Barry, Javorský, Dávid, Krubiński, Mateusz, Lam, Tsz Kin, Ma, Xutai, Mathur, Prashant, Matusov, Evgeny, Maurya, Chandresh, McCrae, John, Murray, Kenton, Nakamura, Satoshi, Negri, Matteo, Niehues, Jan, Niu, Xing, Ojha, Atul Kr., Ortega, John, Papi, Sara, Polák, Peter, Pospíšil, Adam, Pecina, Pavel, Salesky, Elizabeth, Sethiya, Nivedita, Sarkar, Balaram, Shi, Jiatong, Sikasote, Claytone, Sperber, Matthias, Stüker, Sebastian, Sudoh, Katsuhito, Thompson, Brian, Turchi, Marco, Waibel, Alex, Watanabe, Shinji, Wilken, Patrick, Zemánek, Petr, Zevallos, Rodolfo
This paper reports on the shared tasks organized by the 21st IWSLT Conference. The shared tasks address 7 scientific challenges in spoken language translation: simultaneous and offline translation, automatic subtitling and dubbing, speech-to-speech t
Externí odkaz:
http://arxiv.org/abs/2411.05088
Large Language Models (LLMs) have shown remarkable capabilities in natural language processing but exhibit significant performance gaps among different languages. Most existing approaches to address these disparities rely on pretraining or fine-tunin
Externí odkaz:
http://arxiv.org/abs/2410.12462
Large language models (LLMs) have started to play a vital role in modelling speech and text. To explore the best use of context and multiple systems' outputs for post-ASR speech emotion prediction, we study LLM prompting on a recent task named GenSEC
Externí odkaz:
http://arxiv.org/abs/2410.03312
Autor:
Ji, Shaoxiong, Li, Zihao, Paul, Indraneil, Paavola, Jaakko, Lin, Peiqin, Chen, Pinzhen, O'Brien, Dayyán, Luo, Hengyu, Schütze, Hinrich, Tiedemann, Jörg, Haddow, Barry
In this work, we introduce EMMA-500, a large-scale multilingual language model continue-trained on texts across 546 languages designed for enhanced multilingual performance, focusing on improving language coverage for low-resource languages. To facil
Externí odkaz:
http://arxiv.org/abs/2409.17892
Autor:
Martins, Pedro Henrique, Fernandes, Patrick, Alves, João, Guerreiro, Nuno M., Rei, Ricardo, Alves, Duarte M., Pombal, José, Farajian, Amin, Faysse, Manuel, Klimaszewski, Mateusz, Colombo, Pierre, Haddow, Barry, de Souza, José G. C., Birch, Alexandra, Martins, André F. T.
The quality of open-weight LLMs has seen significant improvement, yet they remain predominantly focused on English. In this paper, we introduce the EuroLLM project, aimed at developing a suite of open-weight multilingual LLMs capable of understanding
Externí odkaz:
http://arxiv.org/abs/2409.16235
The COMET metric has blazed a trail in the machine translation community, given its strong correlation with human judgements of translation quality. Its success stems from being a modified pre-trained multilingual model finetuned for quality assessme
Externí odkaz:
http://arxiv.org/abs/2408.15366
Autor:
Iyer, Vivek, Malik, Bhavitvya, Stepachev, Pavel, Chen, Pinzhen, Haddow, Barry, Birch, Alexandra
Despite the recent popularity of Large Language Models (LLMs) in Machine Translation (MT), their performance in low-resource languages (LRLs) still lags significantly behind Neural Machine Translation (NMT) models. In this work, we explore what it wo
Externí odkaz:
http://arxiv.org/abs/2408.12780
Autor:
Kocmi, Tom, Avramidis, Eleftherios, Bawden, Rachel, Bojar, Ondrej, Dvorkovich, Anton, Federmann, Christian, Fishel, Mark, Freitag, Markus, Gowda, Thamme, Grundkiewicz, Roman, Haddow, Barry, Karpinska, Marzena, Koehn, Philipp, Marie, Benjamin, Murray, Kenton, Nagata, Masaaki, Popel, Martin, Popovic, Maja, Shmatova, Mariya, Steingrímsson, Steinþór, Zouhar, Vilém
This is the preliminary ranking of WMT24 General MT systems based on automatic metrics. The official ranking will be a human evaluation, which is superior to the automatic ranking and supersedes it. The purpose of this report is not to interpret any
Externí odkaz:
http://arxiv.org/abs/2407.19884
Autor:
Mazzucato, Camilla, Coscia, Michele, Doğu, Ayça Küçükakdağ, Haddow, Scott, Kılıç, Muhammed Sıddık, Yüncü, Eren, Somel, Mehmet
Recent advances in archaeogenomics have granted access to previously unavailable biological information with the potential to further our understanding of past social dynamics at a range of scales. However, to properly integrate these data within arc
Externí odkaz:
http://arxiv.org/abs/2406.19149