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Found 4 papers, 1 papers with code
Optimizing LLM-Based Multi-Agent System with Textual Feedback: A Case Study on Software Development
Overall, we demonstrate the effectiveness of our optimization method for role-based multi-agent systems tackling software development tasks evaluated on diverse evaluation dimensions, and we investigate the impact of diverse optimization settings on group behaviors of the multi-agent systems to provide practical insights for future development.
A Study on Leveraging Search and Self-Feedback for Agent Reasoning
In this study, we investigate how search and model's self-feedback can be leveraged for reasoning tasks.
General Purpose Verification for Chain of Thought Prompting
Many of the recent capabilities demonstrated by Large Language Models (LLMs) arise primarily from their ability to exploit contextual information.
droidlet: modular, heterogenous, multi-modal agents
In recent years, there have been significant advances in building end-to-end Machine Learning (ML) systems that learn at scale.
