Bayesian Filtering Transformer reframes attention as precision-weighted kriging and residual connections as Kalman updates, delivering gains on cold-start recommendation and noisy LLM fine-tuning tasks.
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UniPrefill accelerates LLM prefill via block-wise dynamic sparsification, achieving up to 2.1x TTFT speedup while supporting hybrid architectures and native vLLM continuous batching.
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Precision Tracked Transformer via Kalman Filtering, Kriging and Process Noise
Bayesian Filtering Transformer reframes attention as precision-weighted kriging and residual connections as Kalman updates, delivering gains on cold-start recommendation and noisy LLM fine-tuning tasks.
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UniPrefill: Universal Long-Context Prefill Acceleration via Block-wise Dynamic Sparsification
UniPrefill accelerates LLM prefill via block-wise dynamic sparsification, achieving up to 2.1x TTFT speedup while supporting hybrid architectures and native vLLM continuous batching.