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

DERA is a paradigm made possible by the increased conversational abilities of LLMs, namely GPT- 4. It provides a simple, interpretable forum for models to communicate feedback and iteratively improve output. We frame our dialog as a discussion between two agent types – a Researcher, who processes information and identifies crucial problem components, and a Decider, who has the autonomy to integrate the Researcher’s information and makes judgments on the final output.