Large language models (LLMs) have demonstrated extraordinary capabilities and
contributed to multiple fields, such as generating and summarizing text, language …

Recent studies have indicated that foundation models, such as BERT and GPT, excel at
adapting to various downstream tasks. This adaptability has made them a dominant force in …

Abstract We introduce Graph of Thoughts (GoT): a framework that advances prompting
capabilities in large language models (LLMs) beyond those offered by paradigms such as …

In this paper, we experimentally evaluate the zero-shot performance of GPT-4 against prior
generations of GPT on the entire uniform bar examination (UBE), including not only the …

Pre-trained large language models (“LLMs”) like GPT-3 can engage in fluent, multi-turn
instruction-taking out-of-the-box, making them attractive materials for designing natural …

Believable proxies of human behavior can empower interactive applications ranging from
immersive environments to rehearsal spaces for interpersonal communication to prototy** …

This survey reviews works in which language models (LMs) are augmented with reasoning
skills and the ability to use tools. The former is defined as decomposing a potentially …

Generative language models have improved drastically, and can now produce realistic text
outputs that are difficult to distinguish from human-written content. For malicious actors …

Reasoning, as an essential ability for complex problem-solving, can provide back-end
support for various real-world applications, such as medical diagnosis, negotiation, etc. This …

Recent efforts have augmented large language models (LLMs) with external resources (eg,
the Internet) or internal control flows (eg, prompt chaining) for tasks requiring grounding or …