Group Cognition Learning: Making Everything Better Through Governed Two-Stage Agents Collaboration

Centralized multimodal learning commonly compresses language, acoustic, and visual signals into a single fused representation for prediction. While effective, this paradigm suffers from two limitations: modality dominance, where optimization gravitates towards the path of least resistance, ignoring weaker but informative modalities, and spurious modality coupling, where models overfit to incidental cross-modal correlations. To address these, we propose Group Cognition Learning (GCL), a governed

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ethics.ai (1 May 2026), “Group Cognition Learning: Making Everything Better Through Governed Two-Stage Agents Collaboration,” evidence record 5133, https://ethics.ai/record/5133 (originally published by arXiv).

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