| SPViT: Enabling Faster Vision Transformers via Soft Token Pruning Z Kong*, P Dong*, X Ma, X Meng, W Niu, M Sun, B Ren, M Qin, H Tang, ... 2022 ECCV, 2022 | 117* | 2022 |
| Rtmobile: Beyond real-time mobile acceleration of rnns for speech recognition P Dong, S Wang, W Niu, C Zhang, S Lin, Z Li, Y Gong, B Ren, X Lin, ... 2020 DAC, 1-6, 2020 | 56 | 2020 |
| NS-FDN: Near-sensor processing architecture of feature-configurable distributed network for beyond-real-time always-on keyword spotting Q Li, C Liu, P Dong, Y Zhang, T Li, S Lin, M Yang, F Qiao, Y Wang, L Luo, ... 2021 TCSI 68 (5), 1892-1905, 2021 | 22 | 2021 |
| Quantum Neural Network Compression Z Hu, P Dong, Z Wang, Y Lin, Y Wang, W Jiang 2022 ICCAD, 2022 | 21 | 2022 |
| Csb-rnn: A faster-than-realtime rnn acceleration framework with compressed structured blocks R Shi*, P Dong*, T Geng, Y Ding, X Ma, HKH So, M Herbordt, A Li, ... 2020 ICS, 1-12, 2020 | 21 | 2020 |
| HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers P Dong, M Sun, A Lu, Y Xie, K Liu, Z Kong, X Meng, Z Li, X Lin, Z Fang, ... 2023 HPCA, 2022 | 18 | 2022 |
| Grim: A general, real-time deep learning inference framework for mobile devices based on fine-grained structured weight sparsity W Niu, Z Li, X Ma, P Dong, G Zhou, X Qian, X Lin, Y Wang, B Ren 2021 TPAMI 44 (10), 6224-6239, 2021 | 18 | 2021 |
| Darb: A density-adaptive regular-block pruning for deep neural networks R Ao, Z Tao, W Yuhao, L Sheng, D Peiyan, C Yen-kuang, X Yuan, ... 2020 AAAI 34 (04), 5495-5502, 2020 | 12 | 2020 |
| Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training Z Kong, H Ma, G Yuan, M Sun, Y Xie, P Dong, X Meng, X Shen, H Tang, ... 2023 AAAI, 2022 | 9 | 2022 |
| Zhenglun Kong, Xin Meng, Zhengang Li, Xue Lin, Zhenman Fang, et al. Heatvit: Hardware-efficient adaptive token pruning for vision transformers P Dong, M Sun, A Lu, Y Xie, K Liu 2023 IEEE International Symposium on High-Performance Computer Architecture …, 2022 | 8 | 2022 |
| TAAS: A timing-aware analytical strategy for AQFP-Capable placement automation P Dong, Y Xie, H Li, M Sun, O Chen, N Yoshikawa, Y Wang 2022 DAC, 1321-1326, 2022 | 7 | 2022 |
| The Lottery Ticket Hypothesis for Vision Transformers X Shen, Z Kong, M Qin, P Dong, G Yuan, X Meng, H Tang, X Ma, Y Wang 2022 IJCAI, 2022 | 5* | 2022 |
| PackQViT: Faster Sub-8-bit Vision Transformers via Full and Packed Quantization on the Mobile P Dong, L Lu, C Wu, C Lyu, G Yuan, H Tang, Y Wang 2023 Neurips, 2023 | 4 | 2023 |
| Mobile or FPGA? A comprehensive evaluation on energy efficiency and a unified optimization framework G Yuan*, P Dong*, M Sun*, W Niu, Z Li, Y Cai, J Liu, W Jiang, X Lin, ... 2021 RTAS, 493-496, 2021 | 4* | 2021 |
| Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge X Shen*, P Dong*, L Lu, Z Kong, Z Li, M Lin, C Wu, Y Wang 2024 AAAI, 2023 | 3 | 2023 |
| You Already Have It: A Generator-Free Low-Precision DNN Training Framework Using Stochastic Rounding G Yuan, SE Chang, Q Jin, A Lu, Y Li, Y Wu, Z Kong, Y Xie, P Dong, M Qin, ... 2022 ECCV, 34-51, 2022 | 2 | 2022 |
| EdgeQAT: Entropy and Distribution Guided Quantization-Aware Training for the Acceleration of Lightweight LLMs on the Edge X Shen, Z Kong, C Yang, Z Han, L Lu, P Dong, C Lyu, C Li, X Guo, Z Shu, ... arXiv preprint arXiv:2402.10787, 2024 | 1 | 2024 |
| HotBEV: Hardware-oriented Transformer-based Multi-View 3D Detector for BEV Perception P Dong, Z Kong, X Meng, P Yu, Y Gong, G Yuan, H Tang, Y Wang 2023 Neurips, 2023 | 1 | 2023 |
| SupeRBNN: Randomized Binary Neural Network Using Adiabatic Superconductor Josephson Devices Z Li, G Yuan, T Yamauchi, Z Masoud, Y Xie, P Dong, X Tang, ... 2023 MICRO, 2023 | 1 | 2023 |
| SpeedDETR: Speed-aware Transformers for End-to-end Object Detection P Dong, Z Kong, X Meng, P Zhang, H Tang, Y Wang, CH Chou 2023 ICML, 2023 | 1 | 2023 |
Yanzhi WangNortheastern University在 northeastern.edu 的电子邮件经过验证
