no code implementations • 31 Mar 2024 • Xingxuan Li, Xuan-Phi Nguyen, Shafiq Joty, Lidong Bing
However, our preliminary experiments indicate that the effectiveness of ICL is limited by the length of the input context.
1 code implementation • 1 Dec 2023 • Xuan-Phi Nguyen, Wenxuan Zhang, Xin Li, Mahani Aljunied, Qingyu Tan, Liying Cheng, Guanzheng Chen, Yue Deng, Sen yang, Chaoqun Liu, Hang Zhang, Lidong Bing
Despite the remarkable achievements of large language models (LLMs) in various tasks, there remains a linguistic bias that favors high-resource languages, such as English, often at the expense of low-resource and regional languages.
no code implementations • 20 Jun 2023 • Xuan-Phi Nguyen, Sharifah Mahani Aljunied, Shafiq Joty, Lidong Bing
Large language models (LLMs) are known to effectively perform tasks by simply observing few exemplars.
1 code implementation • 22 May 2023 • Chenhui Shen, Liying Cheng, Xuan-Phi Nguyen, Yang You, Lidong Bing
With the recent undeniable advancement in reasoning abilities in large language models (LLMs) like ChatGPT and GPT-4, there is a growing trend for using LLMs on various tasks.
1 code implementation • 15 May 2023 • Chenhui Shen, Liying Cheng, Xuan-Phi Nguyen, Yang You, Lidong Bing
Pre-trained language models (PLMs) have achieved outstanding achievements in abstractive single-document summarization (SDS).
no code implementations • 26 Oct 2022 • Xuan-Phi Nguyen, Sravya Popuri, Changhan Wang, Yun Tang, Ilia Kulikov, Hongyu Gong
Direct speech-to-speech translation (S2ST) is among the most challenging problems in the translation paradigm due to the significant scarcity of S2ST data.
1 code implementation • 31 May 2022 • Xuan-Phi Nguyen, Shafiq Joty, Wu Kui, Ai Ti Aw
Numerous recent work on unsupervised machine translation (UMT) implies that competent unsupervised translations of low-resource and unrelated languages, such as Nepali or Sinhala, are only possible if the model is trained in a massive multilingual environment, where these low-resource languages are mixed with high-resource counterparts.
no code implementations • ICLR 2022 • Xuan-Phi Nguyen, Hongyu Gong, Yun Tang, Changhan Wang, Philipp Koehn, Shafiq Joty
Modern unsupervised machine translation systems mostly train their models by generating synthetic parallel training data from large unlabeled monolingual corpora of different languages through various means, such as iterative back-translation.
no code implementations • ACL 2021 • Thanh-Tung Nguyen, Xuan-Phi Nguyen, Shafiq Joty, XiaoLi Li
We introduce a generic seq2seq parsing framework that casts constituency parsing problems (syntactic and discourse parsing) into a series of conditional splitting decisions.
1 code implementation • NAACL 2021 • Thanh-Tung Nguyen, Xuan-Phi Nguyen, Shafiq Joty, XiaoLi Li
We introduce a novel top-down end-to-end formulation of document-level discourse parsing in the Rhetorical Structure Theory (RST) framework.
Ranked #1 on Discourse Parsing on RST-DT
no code implementations • ACL 2020 • Thanh-Tung Nguyen, Xuan-Phi Nguyen, Shafiq Joty, Xiao-Li Li
We propose a novel constituency parsing model that casts the parsing problem into a series of pointing tasks.
no code implementations • ACL 2020 • Thanh-Tung Nguyen, Xuan-Phi Nguyen, Shafiq Joty, Xiao-Li Li
We propose Differentiable Window, a new neural module and general purpose component for dynamic window selection.
1 code implementation • 3 Jun 2020 • Xuan-Phi Nguyen, Shafiq Joty, Thanh-Tung Nguyen, Wu Kui, Ai Ti Aw
Recent unsupervised machine translation (UMT) systems usually employ three main principles: initialization, language modeling and iterative back-translation, though they may apply them differently.
no code implementations • ICLR 2020 • Xuan-Phi Nguyen, Shafiq Joty, Steven C. H. Hoi, Richard Socher
Incorporating hierarchical structures like constituency trees has been shown to be effective for various natural language processing (NLP) tasks.
2 code implementations • NeurIPS 2020 • Xuan-Phi Nguyen, Shafiq Joty, Wu Kui, Ai Ti Aw
Our method achieves state-of-the-art BLEU scores of 30. 7 and 43. 7 in the WMT'14 English-German and English-French translation tasks, respectively.
Ranked #9 on Machine Translation on WMT2014 English-German
no code implementations • 25 Sep 2019 • Xuan-Phi Nguyen, Shafiq Joty, Thanh-Tung Nguyen
The attention mechanism is an indispensable component of any state-of-the-art neural machine translation system.