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pro vyhledávání: '"Laleye P"'
In this paper, we introduce the Fongbe to French Speech Translation Corpus (FFSTC) for the first time. This corpus encompasses approximately 31 hours of collected Fongbe language content, featuring both French transcriptions and corresponding Fongbe
Externí odkaz:
http://arxiv.org/abs/2403.05488
Publikováno v:
NTERNET 2024, The Sixteenth International Conference on Evolving Internet, volume 16, pages 6-11
Information retrieval is a rapidly evolving field. However it still faces significant limitations in the scientific and industrial vast amounts of information, such as semantic divergence and vocabulary gaps in sparse retrieval, low precision and lac
Externí odkaz:
http://arxiv.org/abs/2402.13897
Relation extraction task is a crucial and challenging aspect of Natural Language Processing. Several methods have surfaced as of late, exhibiting notable performance in addressing the task; however, most of these approaches rely on vast amounts of da
Externí odkaz:
http://arxiv.org/abs/2306.04203
Publikováno v:
Proceedings of the 1st International Workshop on Multimedia AI against Disinformation (2022)
With the explosive growth of scientific publications, making the synthesis of scientific knowledge and fact checking becomes an increasingly complex task. In this paper, we propose a multi-task approach for verifying the scientific questions based on
Externí odkaz:
http://arxiv.org/abs/2204.12263
Autor:
Chen, Qingyu, Allot, Alexis, Leaman, Robert, Doğan, Rezarta Islamaj, Du, Jingcheng, Fang, Li, Wang, Kai, Xu, Shuo, Zhang, Yuefu, Bagherzadeh, Parsa, Bergler, Sabine, Bhatnagar, Aakash, Bhavsar, Nidhir, Chang, Yung-Chun, Lin, Sheng-Jie, Tang, Wentai, Zhang, Hongtong, Tavchioski, Ilija, Pollak, Senja, Tian, Shubo, Zhang, Jinfeng, Otmakhova, Yulia, Yepes, Antonio Jimeno, Dong, Hang, Wu, Honghan, Dufour, Richard, Labrak, Yanis, Chatterjee, Niladri, Tandon, Kushagri, Laleye, Fréjus, Rakotoson, Loïc, Chersoni, Emmanuele, Gu, Jinghang, Friedrich, Annemarie, Pujari, Subhash Chandra, Chizhikova, Mariia, Sivadasan, Naveen, Lu, Zhiyong
The COVID-19 pandemic has been severely impacting global society since December 2019. Massive research has been undertaken to understand the characteristics of the virus and design vaccines and drugs. The related findings have been reported in biomed
Externí odkaz:
http://arxiv.org/abs/2204.09781
This paper describes our submission on the COVID-19 literature annotation task at Biocreative VII. We proposed an approach that exploits the knowledge of the globally non-optimal weights, usually rejected, to build a rich representation of each label
Externí odkaz:
http://arxiv.org/abs/2111.05808
In medicine, a communicating virtual patient or doctor allows students to train in medical diagnosis and develop skills to conduct a medical consultation. In this paper, we describe a conversational virtual standardized patient system to allow medica
Externí odkaz:
http://arxiv.org/abs/1912.07421
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