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    • Assessing the Unitary RNN as an End-to-End Compositional Model of Syntax 

      Bernardy, J-P; Lappin, S; End-to-End Compositional Models of Vector-Based Semantics, 2022 (E2ECOMPVEC) (Open Publishing Association, 2022-08-10)
      We show that both an LSTM and a unitary-evolution recurrent neural network (URN) can achieve encouraging accuracy on two types of syntactic patterns: context-free long distance agreement, and mildly context-sensitive cross ...
    • Preface 

      Boleda, G; Bekki, D; Chatzikyriakides, S; Clark, S; Coecke, B; Greco, G; Lewis, M; Moortgat, M; Moot, R; Purver, M (arXiv, 2022)
      The workshop End-to-End Compositional Models of Vector-Based Semantics was held at NUI Galway on 15 and 16 August 2022 as part of the 33rd European Summer School in Logic, Language and Information (ESSLLI 2022).