SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

Showing 23262350 of 4891 papers

TitleStatusHype
Is Mamba Effective for Time Series Forecasting?Code3
A lightweight deep learning pipeline with DRDA-Net and MobileNet for breast cancer classification0
EfficientMorph: Parameter-Efficient Transformer-Based Architecture for 3D Image RegistrationCode0
SwinMTL: A Shared Architecture for Simultaneous Depth Estimation and Semantic Segmentation from Monocular Camera ImagesCode1
Hierarchical Provision of Distribution Grid Flexibility with Online Feedback Optimization0
T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token MemoryCode1
MEDPNet: Achieving High-Precision Adaptive Registration for Complex Die Castings0
Multi-criteria Token Fusion with One-step-ahead Attention for Efficient Vision TransformersCode1
Efficient Convolutional Forward Modeling and Sparse Coding in Multichannel Imaging0
FakeWatch: A Framework for Detecting Fake News to Ensure Credible Elections0
TimeMachine: A Time Series is Worth 4 Mambas for Long-term ForecastingCode3
StainFuser: Controlling Diffusion for Faster Neural Style Transfer in Multi-Gigapixel Histology ImagesCode1
Mitigating Data Consistency Induced Discrepancy in Cascaded Diffusion Models for Sparse-view CT Reconstruction0
Hyper-CL: Conditioning Sentence Representations with HypernetworksCode1
Sparse Bayesian Learning-Based Hierarchical Construction for 3D Radio Environment Maps Incorporating Channel Shadowing0
Towards Unified Modeling for Positive and Negative Preferences in Sign-Aware Recommendation0
Deep Learning for In-Orbit Cloud Segmentation and Classification in Hyperspectral Satellite Data0
Application of Distributed Arithmetic to Adaptive Filtering Algorithms: Trends, Challenges and Future0
Efficient Language Model Architectures for Differentially Private Federated Learning0
Harder Tasks Need More Experts: Dynamic Routing in MoE ModelsCode2
Monotone Individual Fairness0
Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object DetectionCode1
An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language ModelsCode4
What Makes Quantization for Large Language Models Hard? An Empirical Study from the Lens of Perturbation0
Efficient dual-scale generalized Radon-Fourier transform detector family for long time coherent integration0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified