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 1041–1050 of 4891 papers

TitleStatusHype
Fourier Low-rank and Sparse Tensor for Efficient Tensor Completion—0
HSRMamba: Efficient Wavelet Stripe State Space Model for Hyperspectral Image Super-ResolutionCode0
Neural-Inspired Advances in Integral Cryptanalysis—0
From Embeddings to Accuracy: Comparing Foundation Models for Radiographic Classification—0
LanTu: Dynamics-Enhanced Deep Learning for Eddy-Resolving Ocean Forecasting—0
CFARNet: Learning-Based High-Resolution Multi-Target Detection for Rainbow Beam Radar—0
Learning to Think: Information-Theoretic Reinforcement Fine-Tuning for LLMs—0
Multi-Robot Task Allocation for Homogeneous Tasks with Collision Avoidance via Spatial Clustering—0
RainPro-8: An Efficient Deep Learning Model to Estimate Rainfall Probabilities Over 8 Hours—0
Near Optimal Best Arm Identification for Clustered Bandits—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified