Papers by Mohammad Malekzadeh

1 papers
ConSensus: Multi-Agent Collaboration for Multimodal Sensing (2026.findings-acl)

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Challenge: Large language models are increasingly grounded in sensor data to perceive and reason about human physiology and the physical world.
Approach: They propose a training-free multi-agent collaboration framework that decomposes multimodal sensing tasks into specialized, modality-aware agents.
Outcome: The proposed framework matches or exceeds debate methods on multimodal sensing benchmarks while achieving 12.7 times reduction in token cost.

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