AEBNAS: Strengthening Exit Branches in Early-Exit Networks through Hardware-Aware Neural Architecture Search

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Robben, Oscar, Khalilian, Saeed, Meratnia, Nirvana
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Early-Exit Neural Networks with Nested Prediction Sets
by: Jazbec, Metod, et al.
Published: (2023)

On-Sensor Convolutional Neural Networks with Early-Exits
by: Shalby, Hazem Hesham Yousef, et al.
Published: (2025)

Attention Consistency Regularization for Interpretable Early-Exit Neural Networks
by: Zhao, Yanhua
Published: (2026)

Bridging Efficiency and Safety: Formal Verification of Neural Networks with Early Exits
by: Elboher, Yizhak Yisrael, et al.
Published: (2025)

Beyond Greedy Exits: Improved Early Exit Decisions for Risk Control and Reliability
by: Bajpai, Divya Jyoti, et al.
Published: (2025)

Temporal Decisions: Leveraging Temporal Correlation for Efficient Decisions in Early Exit Neural Networks
by: Sponner, Max, et al.
Published: (2024)

Hetero-SplitEE: Split Learning of Neural Networks with Early Exits for Heterogeneous IoT Devices
by: Oda, Yuki, et al.
Published: (2025)

SPARQ: Spiking Early-Exit Neural Networks for Energy-Efficient Edge AI
by: Patne, Parth, et al.
Published: (2026)

NACHOS: Neural Architecture Search for Hardware Constrained Early Exit Neural Networks
by: Gambella, Matteo, et al.
Published: (2024)

Dynamic Vocabulary Pruning in Early-Exit LLMs
by: Vincenti, Jort, et al.
Published: (2024)

S-GRPO: Early Exit via Reinforcement Learning in Reasoning Models
by: Dai, Muzhi, et al.
Published: (2025)

SpecExit: Accelerating Large Reasoning Model via Speculative Exit
by: Yang, Rubing, et al.
Published: (2025)

DistrEE: Distributed Early Exit of Deep Neural Network Inference on Edge Devices
by: Peng, Xian, et al.
Published: (2025)

PTEENet: Post-Trained Early-Exit Neural Networks Augmentation for Inference Cost Optimization
by: Lahiany, Assaf, et al.
Published: (2025)

Improving Group Fairness in Knowledge Distillation via Laplace Approximation of Early Exits
by: Fasth, Edvin, et al.
Published: (2025)

Know What You Don't Know: Selective Prediction for Early Exit DNNs
by: Bajpai, Divya Jyoti, et al.
Published: (2025)

One Jump Is All You Need: Short-Cutting Transformers for Early Exit Prediction with One Jump to Fit All Exit Levels
by: Seshadri, Amrit Diggavi
Published: (2025)

Multi-Objective Hardware Aware Neural Architecture Search using Hardware Cost Diversity
by: Sinha, Nilotpal, et al.
Published: (2024)

Federated Learning for Collaborative Inference Systems: The Case of Early Exit Networks
by: Kaplan, Caelin, et al.
Published: (2024)

LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding
by: Elhoushi, Mostafa, et al.
Published: (2024)

Early-Exit meets Model-Distributed Inference at Edge Networks
by: Colocrese, Marco, et al.
Published: (2024)

LEAP: Layer-wise Exit-Aware Pretraining for Efficient Transformer Inference
by: Kapadia, Shashank, et al.
Published: (2026)

Communication-Efficient Federated Learning through Adaptive Weight Clustering and Server-Side Distillation
by: Tsouvalas, Vasileios, et al.
Published: (2024)

DCentNet: Decentralized Multistage Biomedical Signal Classification using Early Exits
by: Li, Xiaolin, et al.
Published: (2025)

DART: Input-Difficulty-AwaRe Adaptive Threshold for Early-Exit DNNs
by: Patne, Parth, et al.
Published: (2026)

TERMINATOR: Learning Optimal Exit Points for Early Stopping in Chain-of-Thought Reasoning
by: Nagle, Alliot, et al.
Published: (2026)

Early-Exit Graph Neural Networks
by: Di Francesco, Andrea Giuseppe, et al.
Published: (2025)

N-vium: Mixture-of-Exits Transformer for Accelerated Exact Generation
by: Lorenc, Aleksander, et al.
Published: (2026)

SAFE-KD: Risk-Controlled Early-Exit Distillation for Vision Backbones
by: Khazem, Salim
Published: (2026)

EE-Tuning: An Economical yet Scalable Solution for Tuning Early-Exit Large Language Models
by: Pan, Xuchen, et al.
Published: (2024)

Rethinking Calibration for Early-Exit Neural Networks
by: Kubaty, Piotr, et al.
Published: (2025)

LYNX: Learning Dynamic Exits for Confidence-Controlled Reasoning
by: Akgül, Ömer Faruk, et al.
Published: (2025)

DAISY: Data Adaptive Self-Supervised Early Exit for Speech Representation Models
by: Lin, Tzu-Quan, et al.
Published: (2024)

Distributed Inference on Mobile Edge and Cloud: An Early Exit based Clustering Approach
by: Bajpai, Divya Jyoti, et al.
Published: (2024)

ATHEENA: A Toolflow for Hardware Early-Exit Network Automation
by: Biggs, Benjamin, et al.
Published: (2023)

LLMForge: Multi-Backend Hardware-Aware Neural Architecture Search with Infinite-Head Attention for Edge Language Models
by: Jiang, Xinting, et al.
Published: (2026)

DeeAD: Dynamic Early Exit of Vision-Language Action for Efficient Autonomous Driving
by: HU, Haibo, et al.
Published: (2025)

Early-Exit with Class Exclusion for Efficient Inference of Neural Networks
by: Wang, Jingcun, et al.
Published: (2023)

Fine-tuning Multimodal Transformers on Edge: A Parallel Split Learning Approach
by: Fudala, Timo, et al.
Published: (2025)

Many-Task Federated Fine-Tuning via Unified Task Vectors
by: Tsouvalas, Vasileios, et al.
Published: (2025)