Zobrazeno 1 - 10
of 123
pro vyhledávání: '"Pham, Nghia"'
Sequence-to-sequence (s2s) models are the basis for extensive work in natural language processing. However, some applications, such as multi-document summarization, multi-modal machine translation, and the automatic post-editing of machine translatio
Externí odkaz:
http://arxiv.org/abs/2006.08748
Multi-document summarization (MDS) aims to compress the content in large document collections into short summaries and has important applications in story clustering for newsfeeds, presentation of search results, and timeline generation. However, the
Externí odkaz:
http://arxiv.org/abs/2005.10070
Akademický článek
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Reference is a crucial property of language that allows us to connect linguistic expressions to the world. Modeling it requires handling both continuous and discrete aspects of meaning. Data-driven models excel at the former, but struggle with the la
Externí odkaz:
http://arxiv.org/abs/1702.01815
Akademický článek
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We propose an interactive multimodal framework for language learning. Instead of being passively exposed to large amounts of natural text, our learners (implemented as feed-forward neural networks) engage in cooperative referential games starting fro
Externí odkaz:
http://arxiv.org/abs/1605.07133
As a first step towards agents learning to communicate about their visual environment, we propose a system that, given visual representations of a referent (cat) and a context (sofa), identifies their discriminative attributes, i.e., properties that
Externí odkaz:
http://arxiv.org/abs/1603.02618
We extend the SKIP-GRAM model of Mikolov et al. (2013a) by taking visual information into account. Like SKIP-GRAM, our multimodal models (MMSKIP-GRAM) build vector-based word representations by learning to predict linguistic contexts in text corpora.
Externí odkaz:
http://arxiv.org/abs/1501.02598
Autor:
Pham, Nghia Duc1 (AUTHOR), Karim, M. A.1,2 (AUTHOR)
Publikováno v:
Drying Technology. 2022, Vol. 40 Issue 16, p3694-3707. 14p. 1 Diagram, 3 Charts, 6 Graphs.
The Progressive Edge Growth (PEG) algorithm is one of the most widely-used method for constructing finite length LDPC codes. In this paper we consider the PEG algorithm together with a scheduling distribution, which specifies the order in which edges
Externí odkaz:
http://arxiv.org/abs/1103.2690