Formal and Neural Models of Pragmatics

• Course codes: COMP 767 (Winter 2024)
• Instructors: Jackie Cheung
• Classroom: Burnside 719A
• Time: Tuesdays and Thursdays, 11:35 am - 12:55 pm
• Links: Ed: announcements, slides + More information

Description

Large language models have displayed an impressive array of skills and behaviours. They are now in deployment in many applications where they directly interface with human users. This motivates the need for further development of models and evaluations related to their ability to process implicit or intended meaning in context, which falls under the field of pragmatics in linguistics.

In this course, we will examine computational models of pragmatics and how NLP systems have been empirically evaluated for their pragmatic reasoning ability. We will discuss classical theories of formal semantics and pragmatics, as well as more recent statistical and neural models. Topics to be covered may include:

• Dynamic semantics (e.g., File Change Semantics; Discourse Representation Theory)
• Reference and coreference; anaphora
• Implicature and presupposition
• Common sense knowledge representation and reasoning
• Discourse structure; coherence modelling
• Information structure; definiteness