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ResearchSeptember 9, 2026

CUSP: Decomposable Collective Uncertainty for Multi-Agent Multimodal Reasoning

arXiv:2609.05708v1 Announce Type: new Abstract: Aggregating heterogeneous vision-language models (VLMs) can improve multimodal reasoning, but neither an individual model's confidence nor that of the aggregated answer measures reliability at the system level. We present CUSP…

Chung-En Johnny Yu, David Garcia, Brian Jalaian, Nathaniel D. Bastian·arXiv — cs.AI
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  • 01.arXiv:2609.05708v1 Announce Type: new Abstract: Aggregating heterogeneous vision-language models (VLMs) can improve multimodal reasoning, but neither an individual model's confidence nor that of the aggregated answer measures reliability at the system level
  • 02.We present CUSP…

This material is provided as an extended analytical summary.

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