Training and Research

Academic staff

Denis Delfitto, Andrea Padovan , Andrea Padovan, Andrea Padovan, Gaetano Fiorin

Credits

2.5

Language

English

Class attendance

Free Choice

Location

Verona e Bolzano

Learning objectives

On successful completion of this module, PhD students will acquire a basic knowledge in the nature and use of Large Language Models (LLM) and recent developments in AI in text analysis and text production

Prerequisites and basic notions

Some basic knowledge in linguistics and in formal language theory

Program

This 10-hour course will introduce students to the key features of Large Language Models (LLMs) and their relationship with natural language.
The course will cover (i) a brief introduction to the basic mathematical notions that are necessary to understand the developments in Machine Learning (ML) that led to LLMs and (ii) a critical discussion of some influential papers that deal with the LLMs’ impact on applied and theoretical linguistics.
More particularly, there have been interesting debates about the models' ability to produce grammatical sentences and understand complex syntactic constructions. Some of the questions that arise are: (i) how can models display such a high level of proficiency in some linguistic domains? (ii) which are the differences (or the commonalities) with human linguistic competence? (iii) in which linguistic domains are models currently underperforming and what could be done to improve their performance? (iv) what are the consequences for theories on language acquisition? (v) how can models impact research methodology in applied and theoretical linguistics?
Some case studies with both ChatGPT and Google Gemini will be presented to showcase the grammatical performance of LLMs. The course will also explore the concept of 'emergent skills' in LLMs and the associated scientific debate

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Didactic methods

n.v.

Learning assessment procedures

PhD Students can choose aspects of the module as topic of their term paper.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Assessment

n.v.

Criteria for the composition of the final grade

n.v.

Scheduled Lessons

When Classroom Teacher topics
Wednesday 22 January 2025
14:00 - 17:00
Duration: 3:00 AM
Palazzo di Lingue - Co-Working [04 - M] Denis Delfitto
Andrea Padovan, Fabio d'Asaro
Linguistica e Large Language Models
Thursday 23 January 2025
10:00 - 12:00
Duration: 2:00 AM
Palazzo di Lingue - T.10 [T.10 - terra] Andrea Padovan Linguistica e Large Language Models
Thursday 23 January 2025
14:00 - 17:00
Duration: 3:00 AM
Palazzo di Lingue - T.10 [T.10 - terra] Denis Delfitto Linguistica e Large Language Models
Friday 24 January 2025
10:00 - 12:00
Duration: 2:00 AM
Palazzo di Lingue - T.10 [T.10 - terra] Andrea Padovan, Gaetano Fiorin Linguistica e Large Language Models

PhD school courses/classes - 2024/2025

Please note: Additional information will be added during the year. Currently missing information is labelled as “TBD” (i.e. To Be Determined).

1. PhD students must obtain a specified number of CFUs each year by attending teaching activities offered by the PhD School.
First and second year students must obtain 8 CFUs. Teaching activities ex DM 226/2021 provide 5 CFUs; free choice activities provide 3 CFUs.
Third year students must obtain 4 CFUs. Teaching activities ex DM 226/2021 provide 2 CFUs; free choice activities provide 2 CFUs.
More information regarding CFUs is found in the Handbook for PhD Students: https://www.univr.it/phd-vademecum

2. Registering for the courses is not required unless explicitly indicated; please consult the course information to verify whether registration is required or not. When registration is actually required, instructions will be sent well in advance. No confirmation e-mail will be sent after signing up. Please do not enquiry: if you entered the requested information, then registration was silently successful.

3. When Zoom links are not explicitly indicated, courses are delivered in presence only.

4. All information we have is published here. Please do not enquiry for missing information or Zoom links: if the information you need is not there, then it means that we don't have it yet. As soon as we get new information, we will promptly publish it on this page.

Summary of training activities

Teaching Activities ex DM 226/2021: Linguistic Activities

Teaching Activities ex DM 226/2021: Research management and Enhancement

Teaching Activities ex DM 226/2021: Statistics and Computer Sciences

Teaching Activities: Free choice

Faculty

A C D G I L M P R S T V

Artoni Daniele

symbol email daniele.artoni@univr.it symbol phone-number +39 045802 8465

Cantarini Sibilla

symbol email sibilla.cantarini@univr.it symbol phone-number +39 045802 8199

Cappellotto Anna

symbol email anna.cappellotto@univr.it symbol phone-number +39 045802 8349

Cipolla Maria Adele

symbol email adele.cipolla@univr.it symbol phone-number +39 045802 8314

Delfitto Denis

symbol email denis.delfitto@univr.it symbol phone-number +39 045802 8114

Melloni Chiara

symbol email chiara.melloni@univr.it symbol phone-number +39 045802 8119

Padovan Andrea

symbol email andrea.padovan@univr.it symbol phone-number +39 045 802 8753

Rabanus Stefan

symbol email stefan.rabanus@univr.it symbol phone-number +39 045802 8490

Tomaselli Alessandra

symbol email alessandra.tomaselli@univr.it symbol phone-number +39 045802 8315

Vender Maria

symbol email maria.vender@univr.it symbol phone-number 0458028114
Course lessons
PhD Schools lessons

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Guidelines for PhD students

Below you will find the files that contain the Guidelines for PhD students and rules for the acquisition of ECTS credits (in Italian: "CFU") for the Academic Year 2024/2025.

Documents