Гибридные модели

A range of approaches to the representa- tion of lexical semantics have been explored within Computational Linguistics. Two of the most popular are distributional and knowledge- based models. This paper …...

Language models (LMs) are statistical mod- els that calculate probabilities over sequences of words or other discrete symbols. Currently two major paradigms for language model- ing exist: count-based n-gram models, …...

Passage-level question answer matching is a challenging task since it requires effec- tive representations that capture the com- plex semantic relations between questions and answers. In this work, we propose …...

Neural network-based dialog systems are attracting increasing attention in both academia and industry. Recently, researchers have begun to realize the importance of speaker modeling in neural dialog systems, but there …...

AbstractWe report two essential improvements in readability assessment: 1. three novel features in advanced semantics and 2. the timely evidence that traditional ML models (e.g. Random Forest, using handcrafted features) …...

Recent studies in automatic readability assess- ment have shown that hybrid models — mod- els that leverage both linguistically motivated features and neural models — can outperform neural models. However, …...