Words with Consistent Diachronic Usage Patterns are Learned Earlier: A Computational Analysis Using Temporally Aligned Word Embeddings.

In this study, we use temporally aligned word embeddings and a large diachronic corpus of English to quantify language change in a data‐driven, scalable way, which is grounded in language use.

FEEL-IT: Emotion and Sentiment Classification for the Italian Language

Sentiment analysis is a common task to understand people's reactions online. Still, we often need more nuanced information: is the post negative because the user is angry or because they are sad? An abundance of approaches has been introduced for …

Towards bridging the neuro-symbolic gap: deep deductive reasoners.

Symbolic knowledge representation and reasoning and deep learning are fundamentally different approaches to artificial intelligence with complementary capabilities. The former are transparent and data-efficient, but they are sensitive to noise and …