Livnium: A New NLI Classifier Using Attractor Dynamics
Livnium is an NLI classifier that replaces traditional attention mechanisms with attractor dynamics, achieving 428 times faster inference than BERT and 77% accuracy on SNLI without using transformers. The model employs a sequence of geometry-aware state updates to converge to label basins, demonstrating provable local contraction and unique force geometry.
Details
Livnium is an NLI classifier that replaces traditional attention mechanisms with attractor dynamics, achieving 428 times faster inference than BERT and 77% accuracy on SNLI without using transformers. The model employs a sequence of geometry-aware state updates to converge to label basins, demonstrating provable local contraction and unique force geometry.
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