184 citations · 617 across the 22 of their papers we have counts for
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Graph-Induced Syntactic-Semantic Spaces in Transformer-Based Variational AutoEncoders
Yingji Zhang, Marco Valentino, Danilo S. Carvalho +2
The injection of syntactic information in Variational AutoEncoders (VAEs) has been shown to result in an overall improvement of performances and generalisation. An effective strate…
Towards Controllable Natural Language Inference through Lexical Inference Types
Yingji Zhang, Danilo S. Carvalho, Ian Pratt-Hartmann +1
Explainable natural language inference aims to provide a mechanism to produce explanatory (abductive) inference chains which ground claims to their supporting premises. A recent co…
Learning Disentangled Semantic Spaces of Explanations via Invertible Neural Networks
Yingji Zhang, Danilo S. Carvalho, André Freitas
Disentangled latent spaces usually have better semantic separability and geometrical properties, which leads to better interpretability and more controllable data generation. While…
Can Transformers Reason in Fragments of Natural Language?
Viktor Schlegel, Kamen V. Pavlov, Ian Pratt-Hartmann
State-of-the-art deep-learning-based approaches to Natural Language Processing (NLP) are credited with various capabilities that involve reasoning with natural language texts. In t…