Generative AI (GenAI) represents a shift from AI's ability to “recognize” to its ability to
“generate” solutions for a wide range of tasks. As generated solutions and applications grow …

Large language models (LLMs) have been shown to be able to perform new tasks based on
a few demonstrations or natural language instructions. While these capabilities have led to …

Scaling up language models has been shown to predictably improve performance and
sample efficiency on a wide range of downstream tasks. This paper instead discusses an …

Large-scale pretrained language models (LMs) are said to “lack the ability to connect
utterances to the world”(Bender and Koller,), because they do not have “mental models of …

This paper delves into the capabilities of large language models (LLMs), specifically
focusing on advancing the theoretical comprehension of chain-of-thought prompting. We …

Representational spaces learned via language modeling are fundamental to Natural
Language Processing (NLP), however there has been limited understanding regarding how …

Large-scale pretrained language models (LMs) are said to``lack the ability to connect [their]
utterances to the world''(Bender and Koller, 2020). If so, we would expect LM …

Large language models (LLMs) have been shown to be able to perform new tasks based on
a few demonstrations or natural language instructions. While these capabilities have led to …

Large language models (LLMs) have become a dominant approach in natural language
processing, yet their internal knowledge structures remain largely unexplored. In this paper …

Emergent effect is crucial to the understanding of the properties of complex systems that do
not appear in their basic units, but there has been a lack of theories to measure and …