Alessio Miaschi
Research Subjects
Alessio Miaschi has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Claudia Roberta Combei
University of Pavia
2 shared publications - Gabriele Sarti
Aston University University of Bologna University of Trento University of Pisa University of Trieste University of Groningen
2 shared publications - Lucia Busso
Aston University
2 shared publications - Lucio Messina
Aston University University of Bologna University of Trento University of Pisa University of Trieste University of Groningen
2 shared publications - Ludovica Pannitto
CIMeC/DISI CIMeC University of Trento University of Trento
2 shared publications - Malvina Nissim
University of Groningen The Netherlands
2 shared publications
Latest Publications
- Open Access
Teaching NLP with Bracelets and Restaurant Menus: An Interactive Workshop for Italian Students
Although Natural Language Processing (NLP) is at the core of many tools young people use in their everyday life, high school curricula (in Italy) do not include any computational linguistics education. This lack of exposure makes the use of such tools less responsible than it could be and makes choosing computational linguistics as a university degree unlikely. To raise awareness, curiosity, and longer-term interest in young people, we have developed an interactive workshop designed to illustrate the basic principles of NLP and computational linguistics to high school Italian students aged between 13 and 18 years. The workshop takes the form of a game in which participants play the role of machines needing to solve some of the most common problems a computer faces in understanding language: from voice recognition to Markov chains to syntactic parsing. Participants are guided through the workshop with the help of instructors, who present the activities and explain core concepts from computational linguistics. The workshop was presented at numerous outlets in Italy between 2019 and 2021, both face-to-face and online.
Open AccessTeaching NLP with Bracelets and Restaurant Menus: An Interactive Workshop for Italian Students
Although Natural Language Processing (NLP) is at the core of many tools young people use in their everyday life, high school curricula (in Italy) do not include any computational linguistics education. This lack of exposure makes the use of such tools less responsible than it could be and makes choosing computational linguistics as a university degree unlikely. To raise awareness, curiosity, and longer-term interest in young people, we have developed an interactive workshop designed to illustrate the basic principles of NLP and computational linguistics to high school Italian students aged between 13 and 18 years. The workshop takes the form of a game in which participants play the role of machines needing to solve some of the most common problems a computer faces in understanding language: from voice recognition to Markov chains to syntactic parsing. Participants are guided through the workshop with the help of instructors, who present the activities and explain core concepts from computational linguistics. The workshop was presented at numerous outlets in Italy between 2019 and 2021, both face-to-face and online.
- Open Access
A dissemination workshop for introducing young Italian students to NLP
We describe and make available the game-based material developed for a laboratory run at several Italian science festivals to popularize NLP among young students.
Open AccessA dissemination workshop for introducing young Italian students to NLP
We describe and make available the game-based material developed for a laboratory run at several Italian science festivals to popularize NLP among young students.
- Open Access
Linguistic Profiling of a Neural Language Model
In this paper we investigate the linguistic knowledge learned by a Neural Language Model (NLM) before and after a fine-tuning process and how this knowledge affects its predictions during several classification problems. We use a wide set of probing tasks, each of which corresponds to a distinct sentence-level feature extracted from different levels of linguistic annotation. We show that BERT is able to encode a wide range of linguistic characteristics, but it tends to lose this information when trained on specific downstream tasks. We also find that BERT's capacity to encode different kind of linguistic properties has a positive influence on its predictions: the more it stores readable linguistic information of a sentence, the higher will be its capacity of predicting the expected label assigned to that sentence.
Open AccessLinguistic Profiling of a Neural Language Model
In this paper we investigate the linguistic knowledge learned by a Neural Language Model (NLM) before and after a fine-tuning process and how this knowledge affects its predictions during several classification problems. We use a wide set of probing tasks, each of which corresponds to a distinct sentence-level feature extracted from different levels of linguistic annotation. We show that BERT is able to encode a wide range of linguistic characteristics, but it tends to lose this information when trained on specific downstream tasks. We also find that BERT's capacity to encode different kind of linguistic properties has a positive influence on its predictions: the more it stores readable linguistic information of a sentence, the higher will be its capacity of predicting the expected label assigned to that sentence.