SE-Attn and HyLoRA fine-tune hybrid SSMs on sequences up to 8x the pre-training length, approaching full-attention performance at lower cost.
Transformers are ssms: generalized models and efficient algorithms through structured state space duality
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Expansion Span: Combining Fading Memory and Retrieval in Hybrid State Space Models
SE-Attn and HyLoRA fine-tune hybrid SSMs on sequences up to 8x the pre-training length, approaching full-attention performance at lower cost.