The exponential growth of textual data across various domains necessitates the
development of efficient and accurate summarization techniques to facilitate quick …

Enabling large language models (LLMs) to perform tasks in zero-shot has been an
appealing goal owing to its labor-saving (ie, requiring no task-specific annotations); as such …

Recent advancements in Large Language Models (LLMs) and Prompt Engineering have
made chatbot customization more accessible, significantly reducing barriers to tasks that …

Conversational interfaces powered by Large Language Models (LLMs) have recently
become a popular way to obtain feedback during document editing. However, standard chat …

Large language models (LLMs) are incredibly powerful at comprehending and generating
data in the form of text, but are brittle and error-prone. There has been an advent of toolkits …

Large language models (LLMs) are increasingly capable and prevalent, and can be used to
produce creative content. The quality of content is influenced by the prompt used, with more …

Large language models (LLMs) are increasing in capability and popularity, propelling their
application in new domains--including as replacements for human participants in …

LLM chains enable complex tasks by decomposing work into a sequence of sub-tasks.
Crowdsourcing workflows similarly decompose complex tasks into smaller tasks for human …

Generative AI brings novel and impressive abilities to help people in everyday tasks. There
are many AI workflows that solve real and complex problems by chaining AI outputs together …

Recent studies have demonstrated the effectiveness of Large Language Models (LLMs) as
reasoning modules that can deconstruct complex tasks into more manageable sub-tasks …