
Mamba-Timeformer
Uses Mamba state-space models for long-term dependencies, with channel attention and cross-attention fusion to improve long-term battery health prediction.
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Uses Mamba state-space models for long-term dependencies, with channel attention and cross-attention fusion to improve long-term battery health prediction.
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Evaluates and filters content before cache write-back to reduce contamination from low-quality retrieval and improve generation quality and system stability.
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Combines LoRA and mixture-of-experts routing to study parameter-efficient fine-tuning under limited compute and transfer the model to long-term time-series forecasting.
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