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5 papers · 2 filters
Cross-lingual, Character-Level Neural Morphological Tagging
Ryan Cotterell, Georg Heigold
Even for common NLP tasks, sufficient supervision is not available in many languages -- morphological tagging is no exception. In the work presented here, we explore a transfer lea…
Dynamic Integration of Background Knowledge in Neural NLU Systems
Dirk Weissenborn, Tomáš Kočiský, Chris Dyer
Common-sense and background knowledge is required to understand natural language, but in most neural natural language understanding (NLU) systems, this knowledge must be acquired f…
How Robust Are Character-Based Word Embeddings in Tagging and MT Against Wrod Scramlbing or Randdm Nouse?
Georg Heigold, Günter Neumann, Josef van Genabith
This paper investigates the robustness of NLP against perturbed word forms. While neural approaches can achieve (almost) human-like accuracy for certain tasks and conditions, they…
An Empirical Analysis of NMT-Derived Interlingual Embeddings and their Use in Parallel Sentence Identification
Cristina España-Bonet, Ádám Csaba Varga, Alberto Barrón-Cedeño +1
End-to-end neural machine translation has overtaken statistical machine translation in terms of translation quality for some language pairs, specially those with large amounts of p…
Making Neural QA as Simple as Possible but not Simpler
Dirk Weissenborn, Georg Wiese, Laura Seiffe
Recent development of large-scale question answering (QA) datasets triggered a substantial amount of research into end-to-end neural architectures for QA. Increasingly complex syst…