CoWeaver: A Bidirectional Matching Engine for Human-Agent Science Collaboration
Researchers introduce CoWeaver, a bidirectional, learnable, and explainable algorithm designed to match scientists and LLM-based agents for collaborative scientific work. The system uses two-stage ranking and uncertainty-aware capability estimates to form effective teams, and combines exploration and greedy selection strategies. Experimental results show that CoWeaver outperforms baseline methods in matching quality and efficiency across evaluated metrics.
Why it matters: This work advances the formation of effective human-AI teams in scientific research, addressing challenges in dynamic and interpretable collaboration.
Full story at: arXiv AI/ML ↗