3 accepted papers
Prompts to large language models (LLMs) have evolved beyond simple user questions. For LLMs to solve complex problems, today’s practices are to include domain-specific instructions, illustration of tool usages, and/or long context such as textbook chapters in prompts. As such, many parts of prompts…
Large language models are increasingly integrated with external environments, tools, and agents like ChatGPT plugins to extend their capability beyond language-centric tasks. However, today's LLM inference systems are designed for standalone LLMs. They treat each external interaction as the end of L…
With the rise of pre-trained language models, few-shot learning has experienced significant progress in terms of performance. Nevertheless, there remains considerable scope for improvement. The objective of this study is to improve the efficacy of few-shot learning by introducing an enhanced prompt…