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SPViT: Enabling Faster Vision Transformers via Soft Token Pruning., , , , , , , , , и . CoRR, (2021)EdgeQAT: Entropy and Distribution Guided Quantization-Aware Training for the Acceleration of Lightweight LLMs on the Edge., , , , , , , , , и 4 other автор(ы). CoRR, (2024)GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices Based on Fine-Grained Structured Weight Sparsity., , , , , , , , и . IEEE Trans. Pattern Anal. Mach. Intell., 44 (10): 6224-6239 (2022)Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge., , , , , , , и . AAAI, стр. 18944-18951. AAAI Press, (2024)Puncturing the memory wall: Joint optimization of network compression with approximate memory for ASR application., , , , , , и . ASP-DAC, стр. 505-511. ACM, (2021)CSB-RNN: a faster-than-realtime RNN acceleration framework with compressed structured blocks., , , , , , , , и . ICS, стр. 24:1-24:12. ACM, (2020)TAAS: a timing-aware analytical strategy for AQFP-capable placement automation., , , , , , и . DAC, стр. 1321-1326. ACM, (2022)Mobile or FPGA? A Comprehensive Evaluation on Energy Efficiency and a Unified Optimization Framework., , , , , , , , , и 3 other автор(ы). ACM Trans. Embed. Comput. Syst., 21 (5): 65:1-65:22 (сентября 2022)RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition., , , , , , , , , и 1 other автор(ы). CoRR, (2020)HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers., , , , , , , , , и 1 other автор(ы). CoRR, (2022)