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Wendong Fan

2 accepted papers

2026

Graph-of-Agents: A Graph-based Framework for Multi-Agent LLM Collaboration

ICLR 2026poster

With an ever-growing zoo of LLMs and benchmarks, the need to orchestrate multiple models for improved task performance has never been more pressing. While frameworks like Mixture-of-Agents (MoA) attempt to coordinate LLMs, they often fall short in terms of (1) selecting relevant agents, (2) facilita…

Cited by 0SourceScholar
2025

OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation

NeurIPS 2025poster

Large Language Model (LLM)-based multi-agent systems show promise for automating real-world tasks but struggle to transfer across domains due to their domain-specific nature. Current approaches face two critical shortcomings: they require complete architectural redesign and full retraining of all co…

Cited by 0SourcecodeScholar