Why should we add early exits to neural networks?

27 April 2020

Papers citing "Why should we add early exits to neural networks?"

21 / 21 papers shown

Title
Accelerating Large Language Model Inference with Self-Supervised Early Exits Florian Valade LRM 36 1 0 30 Jul 2024
On the Impact of Black-box Deployment Strategies for Edge AI on Latency and Model Performance Jaskirat Singh Emad Fallahzadeh Bram Adams Ahmed E. Hassan MQ 32 3 0 25 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 33 31 0 08 Dec 2023
Adaptive Early Exiting for Collaborative Inference over Noisy Wireless Channels Mikolaj Jankowski Deniz Gunduz K. Mikolajczyk 19 3 0 29 Nov 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 25 1 0 31 Aug 2023
Using Early Exits for Fast Inference in Automatic Modulation Classification E. Mohammed Omar Mashaal H. Abou-zeid 14 3 0 22 Aug 2023
Fixing Overconfidence in Dynamic Neural Networks Lassi Meronen Martin Trapp Andrea Pilzer Le Yang Arno Solin BDL 28 16 0 13 Feb 2023
Anticipate, Ensemble and Prune: Improving Convolutional Neural Networks via Aggregated Early Exits Simone Sarti Eugenio Lomurno Matteo Matteucci 19 4 0 28 Jan 2023
Fast Inference from Transformers via Speculative Decoding Yaniv Leviathan Matan Kalman Yossi Matias LRM 44 618 0 30 Nov 2022
Unsupervised Early Exit in DNNs with Multiple Exits U. HariNarayanN M. Hanawal Avinash Bhardwaj 29 10 0 20 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 22 20 0 09 Jun 2022
Dynamic Split Computing for Efficient Deep Edge Intelligence Arian Bakhtiarnia Nemanja Milošević Qi Zhang Dragana Bajović Alexandros Iosifidis 17 24 0 23 May 2022
A Closer Look at Branch Classifiers of Multi-exit Architectures Shaohui Lin Bo Ji Rongrong Ji Angela Yao 12 4 0 28 Apr 2022
OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses Robik Shrestha Kushal Kafle Christopher Kanan CML 25 13 0 05 Apr 2022
Towards Disentangling Information Paths with Coded ResNeXt Apostolos Avranas Marios Kountouris FAtt 17 1 0 10 Feb 2022
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training Hui-Po Wang Sebastian U. Stich Yang He Mario Fritz FedML AI4CE 28 46 0 11 Oct 2021
Single-Layer Vision Transformers for More Accurate Early Exits with Less Overhead Arian Bakhtiarnia Qi Zhang Alexandros Iosifidis 25 35 0 19 May 2021
Improving the Accuracy of Early Exits in Multi-Exit Architectures via Curriculum Learning Arian Bakhtiarnia Qi Zhang Alexandros Iosifidis 28 12 0 21 Apr 2021
Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss Michael L. Iuzzolino Michael C. Mozer Samy Bengio OOD 13 10 0 19 Feb 2021
AHAR: Adaptive CNN for Energy-efficient Human Activity Recognition in Low-power Edge Devices Nafiul Rashid B. U. Demirel Mohammad Abdullah Al Faruque 11 73 0 03 Feb 2021
Deeply learned face representations are sparse, selective, and robust Yi Sun Xiaogang Wang Xiaoou Tang CVBM 248 921 0 03 Dec 2014