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01/31/2023
Recursive Neural Networks with Bottlenecks Diagnose (Non-)Compositionality
A recent line of work in NLP focuses on the (dis)ability of models to ge...
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10/04/2022
Text Characterization Toolkit
In NLP, models are usually evaluated by reporting single-number performa...
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05/30/2022
Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation
Unlike literal expressions, idioms' meanings do not directly follow from...
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08/12/2021
The paradox of the compositionality of natural language: a neural machine translation case study
Moving towards human-like linguistic performance is often argued to requ...
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04/10/2021
Meta-learning for fast cross-lingual adaptation in dependency parsing
Meta-learning, or learning to learn, is a technique that can help to ove...
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08/22/2019
The compositionality of neural networks: integrating symbolism and connectionism
Despite a multitude of empirical studies, little consensus exists on whe...
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06/04/2019
