Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions

9 June 2021

Papers citing "Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions"

24 / 24 papers shown

Title
Benchmarking Ultra-Low-Power $μ$ NPUs Josh Millar Yushan Huang Sarab Sethi Hamed Haddadi Anil Madhavapeddy BDL 56 0 0 28 Mar 2025
Tiny Models are the Computational Saver for Large Models Qingyuan Wang B. Cardiff Antoine Frappé Benoît Larras Deepu John 29 2 0 26 Mar 2024
EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism Yanxi Chen Xuchen Pan Yaliang Li Bolin Ding Jingren Zhou LRM 15 31 0 08 Dec 2023
Adaptivity and Modularity for Efficient Generalization Over Task Complexity Samira Abnar Omid Saremi Laurent Dinh Shantel Wilson Miguel Angel Bautista ... Vimal Thilak Etai Littwin Jiatao Gu Josh Susskind Samy Bengio 22 5 0 13 Oct 2023
Dynamic nsNet2: Efficient Deep Noise Suppression with Early Exiting Riccardo Miccini Alaa Zniber Clément Laroche Tobias Piechowiak Martin Schoeberl Luca Pezzarossa Ouassim Karrakchou J. Sparsø Mounir Ghogho 13 1 0 31 Aug 2023
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition Samuel Horváth Stefanos Laskaridis Shashank Rajput Hongyi Wang BDL 26 4 0 28 Aug 2023
Mobile Foundation Model as Firmware Jinliang Yuan Chenchen Yang Dongqi Cai Shihe Wang Xin Yuan ... Di Zhang Hanzi Mei Xianqing Jia Shangguang Wang Mengwei Xu 32 19 0 28 Aug 2023
Comparing Humans and Models on a Similar Scale: Towards Cognitive Gender Bias Evaluation in Coreference Resolution Gili Lior Gabriel Stanovsky 24 4 0 24 May 2023
Fixing Overconfidence in Dynamic Neural Networks Lassi Meronen Martin Trapp Andrea Pilzer Le Yang Arno Solin BDL 21 16 0 13 Feb 2023
Adaptive Deep Neural Network Inference Optimization with EENet Fatih Ilhan Ka-Ho Chow Sihao Hu Tiansheng Huang Selim Tekin ... Myungjin Lee Ramana Rao Kompella Hugo Latapie Gan Liu Ling Liu 17 11 0 15 Jan 2023
Federated Learning for Inference at Anytime and Anywhere Zicheng Liu Da Li Javier Fernandez-Marques Stefanos Laskaridis Yan Gao L. Dudziak Stan Z. Li S. Hu Timothy M. Hospedales FedML 16 5 0 08 Dec 2022
Towards Practical Few-shot Federated NLP Dongqi Cai Yaozong Wu Haitao Yuan Shangguang Wang F. Lin Mengwei Xu FedML 19 6 0 01 Dec 2022
The Future of Consumer Edge-AI Computing Stefanos Laskaridis Stylianos I. Venieris Alexandros Kouris Rui Li Nicholas D. Lane 37 8 0 19 Oct 2022
Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs Alexandros Kouris Stylianos I. Venieris Stefanos Laskaridis Nicholas D. Lane 30 8 0 27 Sep 2022
Predictive Exit: Prediction of Fine-Grained Early Exits for Computation- and Energy-Efficient Inference Xiangjie Li Chen Lou Zhengping Zhu Yuchi Chen Yingtao Shen Yehan Ma An Zou 19 20 0 09 Jun 2022
Multi-DNN Accelerators for Next-Generation AI Systems Stylianos I. Venieris C. Bouganis Nicholas D. Lane 13 7 0 19 May 2022
Spike-inspired Rank Coding for Fast and Accurate Recurrent Neural Networks Alan Jeffares Qinghai Guo Pontus Stenetorp Timoleon Moraitis 23 16 0 06 Oct 2021
Smart at what cost? Characterising Mobile Deep Neural Networks in the wild Mario Almeida Stefanos Laskaridis Abhinav Mehrotra L. Dudziak Ilias Leontiadis Nicholas D. Lane HAI 95 44 0 28 Sep 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 176 267 0 26 Feb 2021
It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation Ilias Leontiadis Stefanos Laskaridis Stylianos I. Venieris Nicholas D. Lane 63 29 0 02 Feb 2021
Don't shoot butterfly with rifles: Multi-channel Continuous Speech Separation with Early Exit Transformer Sanyuan Chen Yu-Huan Wu Zhuo Chen Takuya Yoshioka Shujie Liu Jinyu Li 24 26 0 23 Oct 2020
NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications Tien-Ju Yang Andrew G. Howard Bo Chen Xiao Zhang Alec Go Mark Sandler Vivienne Sze Hartwig Adam 88 513 0 09 Apr 2018
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 948 20,471 0 17 Apr 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,109 0 06 Jun 2015