DERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agents

Understand

Large language models (LLMs) have emerged as valuable tools for many natural language understanding tasks.

• In safety-critical applications such as healthcare, the utility of these models is governed by their ability to generate outputs that are factually accurate and complete.
• In this work, we present dialog-enabled resolving agents (DERA).
• DERA is a paradigm made possible by the increased conversational abilities of LLMs, namely GPT-4.