DERA: A New Paradigm for Enhancing LLM Completions (paperswithcode.com)

Summary:

• Dialog-enabled resolving agents (DERA) is a paradigm designed to improve the outputs of large language models (LLMs) in safety-critical applications.
• DERA uses the conversational abilities of GPT-4 to allow models to communicate feedback and iteratively enhance their output in a simple, interpretable forum.

Key terms:

• Dialog-enabled resolving agents (DERA): A paradigm that uses the conversational abilities of LLMs, like GPT-4, to enable models to communicate feedback and iteratively improve output.
• Researcher: An agent type in DERA that processes information and identifies crucial problem components.
• Decider: An agent type in DERA that has the autonomy to integrate the Researcher's information and makes judgments on the final output.
• MedQA dataset: A question-answering dataset that evaluates the performance of LLMs in a medical context.

Tags:

Research GPT-4 Tools Large Language Models conversational AI USMLE Researcher Safety Critical Applications Safety Critical MedQA