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Input Representations for Parsing Discourse Representation Structures: Comparing English with Chinese ...
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On the Difficulty of Translating Free-Order Case-Marking Languages ...
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UDapter: Language Adaptation for Truly Universal Dependency Parsing ...
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Understanding Cross-Lingual Syntactic Transfer in Multilingual Recurrent Neural Networks ...
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Zero-shot Dependency Parsing with Pre-trained Multilingual Sentence Representations ...
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Recurrent Memory Networks for Language Modeling ...
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Abstract:
Recurrent Neural Networks (RNN) have obtained excellent result in many natural language processing (NLP) tasks. However, understanding and interpreting the source of this success remains a challenge. In this paper, we propose Recurrent Memory Network (RMN), a novel RNN architecture, that not only amplifies the power of RNN but also facilitates our understanding of its internal functioning and allows us to discover underlying patterns in data. We demonstrate the power of RMN on language modeling and sentence completion tasks. On language modeling, RMN outperforms Long Short-Term Memory (LSTM) network on three large German, Italian, and English dataset. Additionally we perform in-depth analysis of various linguistic dimensions that RMN captures. On Sentence Completion Challenge, for which it is essential to capture sentence coherence, our RMN obtains 69.2% accuracy, surpassing the previous state-of-the-art by a large margin. ... : 8 pages, 6 figures. Accepted at NAACL 2016 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1601.01272 https://arxiv.org/abs/1601.01272
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Neural versus Phrase-Based Machine Translation Quality: a Case Study ...
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A Survey of Word Reordering in Statistical Machine Translation: Computational Models and Language Phenomena ...
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