This work proposes TileSpMM, which breaks the static-granularity bottleneck through a variable-size tiling algorithm that dynamically adapts to local sparsity patterns, and is equipped with an adaptive load-balancing strategy and customized granularity-specific kernels to improve hardware utilization and mitigate compu...
Hongwei Zeng, Shu-Qin Feng, Hao-Cheng Lian et al.· Proceedings of the Internati...· 0 citations
Sparse Matrix-Matrix Multiplication (SpMM) is a fundamental primitive in scientific computing and artificial intelligence applications. Modern hardware, notably Tensor Core Units (TCUs), offers immense computational power, creating promising opportunities for SpMM acceleration. However, it is difficult to map sparse ma...
Hongwei Zeng, Shu-Qin Feng, Hao-Cheng Lian et al.· Proceedings of the Internati...· 0 citations
The results suggest that lightweight recovery from offline item representations and transparent fusion should be ruled out before improvements are attributed to serving-time language modeling, semantic-ID generation, or heavier semantic machinery.
Kong Wang, Zhongke He, Xiang Chen et al.· 0 citations
Activation Steering Adapter (ASA), a training-free, inference-time controller that performs a single-shot mid-layer intervention and targets tool domains via a router-conditioned mixture of steering vectors with a probe-guided signed gate to amplify true intent while suppressing spurious triggers is proposed.
Youjin Wang, Run Zhou, Rong Fu et al.· 4 citations· ⚡2
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