Zobrazeno 1 - 10
of 45
pro vyhledávání: '"HU Wenpeng"'
Abstract. Automatically generating scientific literature surveys is a valuable task that can significantly enhance research efficiency. However, the diverse and complex nature of information within a literature survey poses substantial challenges for
Externí odkaz:
http://arxiv.org/abs/2408.07884
Events serve as fundamental units of occurrence within various contexts. The processing of event semantics in textual information forms the basis of numerous natural language processing (NLP) applications. Recent studies have begun leveraging large l
Externí odkaz:
http://arxiv.org/abs/2305.15268
This paper studies the problem of detecting novel or unexpected instances in text classification. In traditional text classification, the classes appeared in testing must have been seen in training. However, in many applications, this is not the case
Externí odkaz:
http://arxiv.org/abs/2009.11119
Autor:
Hu, Wenpeng, Wang, Mengyu, Liu, Bing, Ji, Feng, Chen, Haiqing, Zhao, Dongyan, Ma, Jinwen, Yan, Rui
Sparsity is regarded as a desirable property of representations, especially in terms of explanation. However, its usage has been limited due to the gap with dense representations. Most NLP research progresses in recent years are based on dense repres
Externí odkaz:
http://arxiv.org/abs/1911.02914
Information-seeking conversation system aims at satisfying the information needs of users through conversations. Text matching between a user query and a pre-collected question is an important part of the information-seeking conversation in E-commerc
Externí odkaz:
http://arxiv.org/abs/1911.02747
Named entity recognition (NER) is a foundational technology for information extraction. This paper presents a flexible NER framework compatible with different languages and domains. Inspired by the idea of distant supervision (DS), this paper enhance
Externí odkaz:
http://arxiv.org/abs/1908.05009
Existing neural models for dialogue response generation assume that utterances are sequentially organized. However, many real-world dialogues involve multiple interlocutors (i.e., multi-party dialogues), where the assumption does not hold as utteranc
Externí odkaz:
http://arxiv.org/abs/1905.13637
Neural machine translation (NMT) becomes a new approach to machine translation and generates much more fluent results compared to statistical machine translation (SMT). However, SMT is usually better than NMT in translation adequacy. It is therefore
Externí odkaz:
http://arxiv.org/abs/1704.06393
Publikováno v:
In Journal of Adolescence April 2019 72:1-9
Publikováno v:
E3S Web of Conferences, Vol 194, p 01022 (2020)
In this work, an integrated numerical model combining combustion and fluid heating was established for a 660 MW coal-fired boiler. To validate the accuracy of the developed model, related experiment was also conducted, and shows that the relative err
Externí odkaz:
https://doaj.org/article/359ecd9315e74c3f8fa45f0b47b35266