Training and Research
PhD Programme Courses/classes
This page shows the PhD programme's training activities for the academic year 2024/2025 held at the University of Verona. You find the complete course catalogue with all activities held both in Verona and Bolzano at the website of the PhD programme at the Free University of Bolzano:
VinKiamo as a best practice for citizen science: the example of German varieties in the Alps
Credits: 1
Language: English
Teacher: Sabrina Bertollo
Inflectional Morphology (Winter School)
Credits: 2.5
Language: English
Teacher: Stefan Rabanus
Linguistics and Large Language Models
Credits: 2.5
Language: English
Teacher: Andrea Padovan, Denis Delfitto, Gaetano Fiorin, Fabio d'Asaro, Andrea Padovan
Investigating linguistic variables using oral data: the AlpiLinK corpus
Credits: 0.5
Language: English
Teacher: Stefan Rabanus
Mapping linguistic variation with the REDE SprachGIS
Credits: 1.5
Language: English
Teacher: Marina Frank (Philipps-Universität Marburg), Stefan Rabanus
Phraseology and CxG
Credits: 1
Language: German (slides in English)
Teacher: Elmar Schafroth, Sibilla Cantarini
Linguistics and Large Language Models (2024/2025)
Academic staff
Denis Delfitto, Andrea Padovan , Fabio d'Asaro, Andrea Padovan, Andrea Padovan, Gaetano Fiorin
Referent
Credits
2.5
Language
English
Class attendance
Compulsory
Location
VERONA
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
Didactic methods
n.v.
Learning assessment procedures
PhD Students can choose aspects of the module as topic of their term paper.
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 | Linguistics and Large Language Models |
Thursday 23 January 2025 10:00 - 12:00 Duration: 2:00 AM |
Palazzo di Lingue - T.10 [T.10 - terra] | Denis Delfitto | 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] | Denis Delfitto | Linguistica e Large Language Models |