Online education platforms, leveraging the internet to distribute education resources, seek to
provide convenient education but often fall short in real-time communication with students …

Abstract Language models are increasingly being deployed for general problem solving
across a wide range of tasks, but are still confined to token-level, left-to-right decision …

Ever since the Turing Test was proposed in the 1950s, humans have explored the mastering
of language intelligence by machine. Language is essentially a complex, intricate system of …

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 …

This paper provides a survey of the emerging area of Large Language Models (LLMs) for
Software Engineering (SE). It also sets out open research challenges for the application of …

Large-scale task planning is a major challenge. Recent work exploits large language
models (LLMs) directly as a policy and shows surprisingly interesting results. This paper …

Although large language models (LLMs) have demonstrated impressive ability in code
generation, they are still struggling to address the complicated intent provided by humans. It …

Safety is critical to the usage of large language models (LLMs). Multiple techniques such as
data filtering and supervised fine-tuning have been developed to strengthen LLM safety …

Large language models (LLMs) are becoming attractive as few-shot reasoners to solve
Natural Language (NL)-related tasks. However, there is still much to learn about how well …

Recent works like Tree-of-Thought (ToT) and Reasoning via Planning (RAP) aim to augment
the reasoning capabilities of LLMs by using tree-search algorithms to guide multi-step …