Language, Logic, and Machines (LLaMa) Lab
Humans use language to transmit information and to support reasoning. If you ask me how many of the tacos are left, and I say "some", you will defeasibly infer that it's not the case that all are left. This inference depends both on your beliefs about my intentions, but also facts about the meaning of words like "some" and "all", as well as their relations to each other in the language. Even this simple example shows that we need a theory of natural language semantics that explains how people compute the meanings of expressions based on their parts, but also how those meanings become enriched in context in virtue of how interlocutors reason about each others beliefs, goals, and intentions.
Research in the LLaMa lab aims to address this question by combining tools and insights from formal, logic-based approaches to meaning with tools and insights from the field of computational cognitive modeling. In the ideal, the result are theories that combine the richly structured repesentations we believe underlie natural language meaning with a plausible model of how humans learn and perform computations over these representations that accord with behavioral data.
- Graduate Students
Jianrong Yu, GRA
Andrea Maynard, GRA
- Undergraduate Students
Shaun Marie Stienestra
- The semantics and pragmatics of dogwhistle language.
Joint work with Eric McCready that focuses on dogwhistle language---language that sends one message to an outgroup while at the same time sending a second (often taboo, controversial, or inflammatory) message to an ingroup. We explore in a Bayesian game-theoretic setting, the formal properties of dog whistle language and interactional pressures that govern its use.
- Composition and construal in recursive neural networks.
Joint work with Aaron Steven White and Patrick D. Elliot that is exploring computational models of construal to tease apart what factors constrain the possible relations allowed by a predicate.
- Processing secondary content
Stanley Donahoo is working on the processing of secondary content in slurs and expletives using EEG and other behavioral measures.
- Partisianship and the political language of bills.
This research, currently being conducted by Shaun Marie Stienestra, uses tools from nlp to model partisan reaction to bills based on purely stylistic aspects of their construction.
Courses & Workshops
- Seminar in "Computational Semantics and Pragmatics".
This course has two prongs: (i) we consider recent work borrowing formal tools from functional programming and programming language design to model phenomena in natural language semantics, and (ii) we explore recent work in the computational modeling of pragmatic behavior, mostly through Bayesian Rational Speaker Theory, but also other approaches.