Adult semantic memory has been traditionally conceptualized as a relatively static memory
system that consists of knowledge about the world, concepts, and symbols. Considerable …

Language models demonstrate both quantitative improvement and new qualitative
capabilities with increasing scale. Despite their potentially transformative impact, these new …

While vision-and-language models perform well on tasks such as visual question
answering, they struggle when it comes to basic human commonsense reasoning skills. In …

Playing partial information, restricted communication, cooperative (PIRCC) games with
humans have proven challenging for AI, due to our reliance on social dynamics and …

Pragmatic reference enables efficient interpersonal communication. Prior work uses simple
reference games to test models of pragmatic reasoning, often with unidentified speakers and …

Considerable work during the past two decades has focused on modeling the structure of
semantic memory, although the performance of these models in complex and unconstrained …

The multidisciplinary nature of physiology requires students to acquire, retain, apply, and
evaluate knowledge from different scientific disciplines. Optimal learning techniques, such …

Although board games and video games have been studied for decades in artificial
intelligence research, challenging word games remain relatively unexplored. Word games …

Due to the human-like nature, large language models (LLMs) often express uncertainty in
their outputs. This expression, known as” verbalized uncertainty”, can appear in phrases …

Winning the social game Codenames involves combining cooperative and language
understanding capabilities. We developed six cooperative bots designed to play the …