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

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Showing 571–580 of 4891 papers

TitleStatusHype
A Hybrid CNN-BiLSTM Voice Activity DetectorCode1
A State-Space Perspective on Modelling and Inference for Online Skill RatingCode1
Calibrating LLMs with Information-Theoretic Evidential Deep LearningCode1
Gracefully Filtering Backdoor Samples for Generative Large Language Models without RetrainingCode1
Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image ClassificationCode1
Gaussian Kernel Mixture Network for Single Image Defocus DeblurringCode1
Birdie: Advancing State Space Models with Reward-Driven Objectives and CurriculaCode1
CIS-UNet: Multi-Class Segmentation of the Aorta in Computed Tomography Angiography via Context-Aware Shifted Window Self-AttentionCode1
Activation-Informed Merging of Large Language ModelsCode1
FViT: A Focal Vision Transformer with Gabor FilterCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified