TopoPrior learns transferable topology priors offline from multi-domain reference graphs using a conditional variational graph model and adversarial adaptation to initialize collaboration structures for multi-agent LLM systems, reducing online search overhead.
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Interpretability analysis of AV-HuBERT reveals visual-driven clustering of visemes that audio refines, especially for ambiguous cases.
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Learning Transferable Topology Priors for Multi-Agent LLM Collaboration Across Domains
TopoPrior learns transferable topology priors offline from multi-domain reference graphs using a conditional variational graph model and adversarial adaptation to initialize collaboration structures for multi-agent LLM systems, reducing online search overhead.
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Interpreting the Role of Visemes in Audio-Visual Speech Recognition
Interpretability analysis of AV-HuBERT reveals visual-driven clustering of visemes that audio refines, especially for ambiguous cases.