Natural Language Processing

Italian Transformers Under the Linguistic Lens

We investigate whether and how using different architectures of probing models affects the performance of Italian transformers in encoding a wide spectrum of linguistic features.

[email protected] AcCompl-It: Improving Complexity and Acceptability Prediction with Multi-task Learning on Self-Supervised Annotations

This work describes a self-supervised data augmentation approach used to improve learning models' performances when only a moderate amount of labeled data is available.

ETC-NLG: End-to-end Topic-Conditioned Natural Language Generation

We present ETC-NLG, an approach leveraging topic modeling annotations to enable fully-unsupervised End-to-end Topic-Conditioned Natural Language Generation over emergent topics in unlabeled document collections.

ICLR 2020 Trends: Better & Faster Transformers for Natural Language Processing

A summary of promising directions from ICLR 2020 for better and faster pretrained tranformers language models.

Covid-19 Semantic Browser

A semantic browser for SARS-CoV-2 and COVID-19 powered by neural language models.

Neural Language Models: the New Frontier of Natural Language Understanding

An overview of the latest advances in the field of NLP, with a focus on neural models and language understanding.

The Literary Ordnance: When the Writer is an AI

Discussing the applications of AI and NLP in the fields of literature and digital humanities.