Transformer language models have received widespread public attention, yet their
generated text is often surprising even to NLP researchers. In this survey, we discuss over …

The past decade has seen the rapid development of a new approach to pragmatics that
attempts to integrate insights from formal and experimental semantics and pragmatics …

Scalar inferences (SI) are a signature example of how humans interpret language based on
unspoken alternatives. While empirical studies have demonstrated that human SI rates are …

All living beings try to save effort, and humans are no exception. This groundbreaking book
shows how we save time and energy during communication by unconsciously making …

This book investigates the syntax and usage of fragments (Morgan 1973), apparently
subsentential utterances like" A coffee, please!" which fulfill the same communicative …

During communication, the interpretation of utterances is sensitive to a listener's probabilistic
prior beliefs. In this paper, we focus on the influence of prior beliefs on so‐called exhaustivity …

Bayesian accounts of social cognition successfully model the human ability to infer goals
and intentions of others on the basis of their behavior. In this paper, we extend this paradigm …

Formal probabilistic models, such as the Rational Speech Act model, are widely used for
formalizing the reasoning involved in various pragmatic phenomena, and when a model …

Under the Gricean view of communication, cooperative speakers are expected to encode
their messages efficiently. Probabilistic models of pragmatics formalize this requirement via …

State of the art large language models (LLMs) have shown impressive performance on a
variety of benchmark tasks and are increasingly used as components in larger applications …