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token-mixing

topic1 events
papersSEP 10 04:00 UTC

New Relation mechanism decouples relation formation from flow allocation in token mixing

A revised arXiv paper in machine learning introduces Relation, a token-mixing mechanism that splits an operation standard attention fuses into a single score-to-flow step. The method first organizes pairwise evidence into explicit Self and Exchange relations and then allocates information flow across them. The authors position this as an alternative to dominant attention-based token mixing in sequence models.

attention/architecture/deep-learning/transformers