EvalRS: Evaluating Recommender Systems on Many Tests — This article describes a novel data and code challenge that is currently running: EvalRS. We decided to organize EvalRS with friends from Coveo, Microsoft, and NVIDIA, to better understand evaluation in Recommender Systems. Anybody can join the challenge. There are prizes for best systems, best ideas and best student work…

Introduction to CLIP and to how we fine-tuned it for the Italian Language — During July, HuggingFace and Google organized a joint Community week in which interested people could make use of Google TPUs to experiment with project they liked (by also using the JAX library).

Are text properties kept when you transform (e.g., translate) a message in another language? — When you transform a text (i.e., translate, paraphrase, summarize it), you expect the general properties of your message to not change from input to output. For example, you expect your message to be perceived as happy even when translated to another language. Issues can arise when this does not happen…

Reviewing MilaNLP 2021 research papers on reasoning, meaning and language — In this blog post series, we revise what MilaNLP has been doing during 2021, analyzing the main themes of research and which output the team has produced. MilaNLP is the NLP Lab in Milano (Italy) lead by Prof. Dirk Hovy at Bocconi University. The first blog post covered what we…

Reviewing MilaNLP 2021 research papers on text analytics — In this blog post series, we revise what MilaNLP has been doing during 2021, analyzing the main themes of research and which output the team has produced. MilaNLP is the NLP Lab in Milano (Italy) lead by Prof. Dirk Hovy at Bocconi University. The first blog post covered what we…

Reviewing MilaNLP 2021 research papers on bias and ethics. — In this blog post series, we revise what MilaNLP has been doing during 2021, analyzing the main themes of research and which output the team has produced. MilaNLP is the NLP Lab in Milano (Italy) lead by Prof. Dirk Hovy at Bocconi University. This first blog post will cover the…

A little story about how BERT and GPT-2 hide harmful statements inside their weights. — BERT and GPT-2: we all love language models… I mean, who doesn’t? Language models like BERT and GPT-2 (and GPT-3) have had an enormous impact on the entire NLP field. Most of the models that obtained groundbreaking results on the famous GLUE benchmark are based on BERT. …

Introducing FEEL-IT: a data set and a package for sentiment analysis and emotion recognition in Italian. — Sentiment Analysis and Emotion Recognition Recognizing emotions in text is fundamental to get a better sense of how people are talking about something. People can talk about a new event, but positive/negative labels might not be enough. There is a big difference between being angered by something and scared by something. …

Combining BERT and friends with Neural Variational Topic Models — In this blog post, I discuss our latest published paper on topic modeling: Bianchi, F., Terragni, S., Hovy, D., Nozza, D., & Fersini, E. (2021). Cross-lingual Contextualized Topic Models with Zero-shot Learning. European Chapter of the Association for Computational Linguistics (EACL). https://arxiv.org/pdf/2004.07737/ Suppose we have a small set of documents…