Explainable Natural Language Processing with Matrix Product States
Jirawat Tangpanitanon,
Chanatip Mangkang,
Pradeep Bhadola
et al.
Abstract:Despite empirical successes of recurrent neural networks (RNNs) in natural language processing (NLP), theoretical understanding of RNNs is still limited due to intrinsically complex computations in RNNs. We perform a systematic analysis of RNNs' behaviors in a ubiquitous NLP task, the sentiment analysis of movie reviews, via the mapping between a class of RNNs called recurrent arithmetic circuits (RACs) and a matrix product state (MPS). Using the von-Neumann entanglement entropy (EE) as a proxy for information… Show more
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