MECoBench is a benchmark showing that multimodal agent collaboration improves embodied task performance when communication balances coordination costs, with gains also under noisy conditions.
Enhancing diagnostic capability with multi-agents conversational large language models , volume =
2 Pith papers cite this work, alongside 77 external citations. Polarity classification is still indexing.
2
Pith papers citing it
77
external citations · OpenAlex
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Single-agent LLM frameworks outperform naive multi-agent systems in multimodal clinical risk prediction tasks and are better calibrated.
citing papers explorer
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MECoBench: A Systematic Study of Multimodal Agent Collaboration in Embodied Environments
MECoBench is a benchmark showing that multimodal agent collaboration improves embodied task performance when communication balances coordination costs, with gains also under noisy conditions.
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AgentRx: A Benchmark Study of LLM Agents for Multimodal Clinical Prediction Tasks
Single-agent LLM frameworks outperform naive multi-agent systems in multimodal clinical risk prediction tasks and are better calibrated.