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arXiv AI By Won Seok Jang, Harry Bhaskar Joshi, Hong Yu

Does Multi-Agent Collaboration Reduce Hallucination in Clinical Tasks?

Read the original on arXiv AI →

The study investigates whether multi‑agent large language model (LLM) systems reduce hallucination in clinical tasks. By evaluating a single‑LLM baseline and three multi‑agent topologies across four models and three clinical tasks, the authors find that collaboration improves task performance but does not consistently lower hallucination; the effect varies by model rather than by topology or number of agents. A self‑correction experiment further shows that only certain models benefit from collaboration, while others see increased hallucination.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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