We introduce a class of probabilistic continuous translation models called Recurrent
Continuous Translation Models that are purely based on continuous representations for …

Computational semantics has long been considered a field divided between logical and
statistical approaches, but this divide is rapidly eroding with the development of statistical …

The lexicon of any natural language encodes a huge number of distinct word meanings. Just
to understand this article, you will need to know what thousands of words mean. The space …

Machine translation (MT) plays an important role in benefiting linguists, sociologists,
computer scientists, etc. by processing natural language to translate it into some other …

Modelling compositional meaning for sentences using empirical distributional methods has
been a challenge for computational linguists. We implement the abstract categorical model …

This chapter describes how vector space models have been used for document retrieval.
These document‐based models represent the meaning, or topic, of a whole document. It …

This work is concerned with distinguishing different semantic relations which exist between
distributionally similar words. We compare a novel approach based on training a linear …

The compositionality of meaning extends beyond the single sentence. Just as words
combine to form the meaning of sentences, so do sentences combine to form the meaning of …

We introduce a new approach to semantics which combines the benefits of distributional
and formal logical semantics. Distributional models have been successful in modelling the …

Tree-structured recursive neural networks (TreeRNNs) for sentence meaning have been
successful for many applications, but it remains an open question whether the fixed-length …