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cs.DC2026
FlashT2S: GPU-Accelerated Tensor-to-Spike Conversion Operators for Heterogeneous Neuromorphic LLM Backends
Rongyuan Guo, Haotian Wang, Yufeng Zhang +2
Artificial intelligence faces two growing challenges: computational bottlenecks and energy inefficiency inherent to the von Neumann architecture. Neuromorphic computing offers a pr…
cs.DC2026
A-IO: Adaptive Inference Orchestration for Memory-Bound NPUs
Chen Zhang, Yan Ding, Haotian Wang +3
During the deployment of Large Language Models (LLMs), the autoregressive decoding phase on heterogeneous NPU platforms (e.g., Ascend 910B) faces severe memory-bound challenges. Th…
cs.LG2026
MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations
Xianyong Xu, Yuanjun Zuo, Zhihong Huang +4
Time series forecasting is vital across many domains, yet existing models struggle with fixed-length inputs and inadequate multi-scale modeling. We propose MR-CDM, a framework comb…