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edge deployment

62 papers

Papers

Deploying Rapid Damage Assessments from sUAS Imagery for Disaster Response AAAI 2026 EASE: Practical and Efficient Safety Alignment for Small Language Models AAAI 2026 EmoMAS: Emotion-Aware Multi-Agent System for High-Stakes Edge-Deployable Negotiation with Bayesian Orchestration ACL 2026 FastPose-ViT: A Vision Transformer for Real-Time Spacecraft Pose Estimation WACV 2026 FIRM-MoE:Fine-GrainedExpert Decomposition for Resource-Adaptive MoE Inference AAAI 2026 Foundry: Distilling 3D Foundation Models for the Edge CVPR 2026 Pip-Stereo: Progressive Iterations Pruner for Iterative Optimization based Stereo Matching CVPR 2026 SAQ-SAM: Semantically-Aligned Quantization for Segment Anything Model AAAI 2026 SPEED-Q: Staged Processing with Enhanced Distillation Towards Efficient Low-Bit On-Device VLM Quantization AAAI 2026 Towards Robust Edge Model Adaptation via Elastic Architecture Search AAAI 2026 Traffic-R1: Reinforced LLMs Bring Human-Like Reasoning to Traffic Signal Control Systems ACL 2026 Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity ICML 2025 AdMiT: Adaptive Multi-Source Tuning in Dynamic Environments CVPR 2025 AutoLUT: LUT-Based Image Super-Resolution with Automatic Sampling and Adaptive Residual Learning CVPR 2025 Boost Embodied AI Models with Robust Compression Boundary IJCAI 2025 Demystifying Small Language Models for Edge Deployment ACL 2025 DnLUT: Ultra-Efficient Color Image Denoising via Channel-Aware Lookup Tables CVPR 2025 Efficient Unstructured Pruning of Mamba State-Space Models for Resource-Constrained Environments EMNLP 2025 GradQ-ViT: Robust and Efficient Gradient Quantization for Vision Transformers AAAI 2025 Grammar Pruning: Enabling Low-Latency Zero-Shot Task-Oriented Language Models for Edge AI EMNLP 2025 JAQ: Joint Efficient Architecture Design and Low-Bit Quantization with Hardware-Software Co-Exploration AAAI 2025 LitMAS: A Lightweight and Generalized Multi-Modal Anti-Spoofing Framework for Biometric Security Interspeech 2025 MEET: Towards Memory-Efficient Temporal Sparse Deep Neural Networks CVPR 2025 MixA: A Mixed Attention approach with Stable Lightweight Linear Attention to enhance Efficiency of Vision Transformers at the Edge ICCV 2025 MONAQ: Multi-Objective Neural Architecture Querying for Time-Series Analysis on Resource-Constrained Devices EMNLP 2025