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Selective Rotary Position Embedding
Sajad Movahedi, Timur Carstensen, Arshia Afzal +3
Position information is essential for language modeling. In softmax transformers, Rotary Position Embeddings (\textit{RoPE}) encode positions through \textit{fixed-angle} rotations…
MT-NAM: An Efficient and Adaptive Model for Epileptic Seizure Detection
Arshia Afzal, Volkan Cevher, Mahsa Shoaran
Enhancing the accuracy and efficiency of machine learning algorithms employed in neural interface systems is crucial for advancing next-generation intelligent therapeutic devices.…
Linear Attention for Efficient Bidirectional Sequence Modeling
Arshia Afzal, Elias Abad Rocamora, Leyla Naz Candogan +5
Linear Transformers and State Space Models have emerged as efficient alternatives to softmax Transformers for causal sequence modeling, enabling parallel training via matrix multip…