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 4161–4170 of 4891 papers

TitleStatusHype
Distribution-Aware Sampling and Weighted Model Counting for SAT—0
DITTO: Diffusion Inference-Time T-Optimization for Music Generation—0
Diverse super-resolution with pretrained deep hiererarchical VAEs—0
Divide-and-Conquer Strategy for Large-Scale Dynamic Bayesian Network Structure Learning—0
Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning—0
DLCM: a versatile multi-level solver for heterogeneous multicellular systems—0
DMFC-GraspNet: Differentiable Multi-Fingered Robotic Grasp Generation in Cluttered Scenes—0
DMRA: An Adaptive Line Spectrum Estimation Method through Dynamical Multi-Resolution of Atoms—0
DNA cyclization and looping in the wormlike limit: normal modes and the validity of the harmonic approximation—0
DNN-Compressed Domain Visual Recognition with Feature Adaptation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified