Papers with consensus principle

1 papers
EIT: Enhanced Interactive Transformer (2024.acl-long)

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Challenge: Existing multi-view learning models prioritize complementarity while ignoring consensus . EMHA allows for efficient modeling of global dependencies among tokens in parallel .
Approach: They propose an enhanced multi-head self-attention (EMHA) that prioritizes complementarity while ignoring consensus.
Outcome: The proposed method favors consensus among heads by introducing two models . it is superior on a wide range of language tasks with a modest increase in model size .

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