The last two decades have seen a significant amount of interest in bilingual language
learning and processing. A number of computational models have also been developed to …

Deep learning (DL) is increasingly viewed as a foundational methodology for advancing
Artificial Intelligence (AI). However, its interpretability remains limited, and it often …

Can we obtain insights about the brain using AI models? How is the information in deep
learning models related to brain recordings? Can we improve AI models with the help of …

In Transformer-based language models (LMs) the attention mechanism converts token
embeddings into contextual embeddings that incorporate information from neighboring …

Large language models (LLMs) have complicated internal dynamics, but induce
representations of words and phrases whose geometry we can study. Human language …

Are multimodal inputs necessary for grammar induction? Recent work has shown that
multimodal training inputs can improve grammar induction. However, these improvements …

Extractive summaries are usually presented as lists of sentences with no expected cohesion
between them and with plenty of redundant information if not accounted for. In this paper, we …

Product images (eg, a phone) can be used to elicit a diverse set of consumer-reported
features expressed through language, including surface-level perceptual attributes (eg," …