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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 671–680 of 4891 papers

TitleStatusHype
AI Accelerator Survey and TrendsCode1
An MRC Framework for Semantic Role LabelingCode1
Voxel Transformer for 3D Object DetectionCode1
A Simple and Efficient Reconstruction Backbone for Snapshot Compressive ImagingCode1
An Extensible Benchmark Suite for Learning to Simulate Physical SystemsCode1
Token Shift Transformer for Video ClassificationCode1
Multi-scale Matching Networks for Semantic CorrespondenceCode1
Learning Span-Level Interactions for Aspect Sentiment Triplet ExtractionCode1
Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare SettingsCode1
Adaptive wavelet distillation from neural networks through interpretationsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified