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 1831–1840 of 4891 papers

TitleStatusHype
A New Proof for the Linear Filtering and Smoothing Equations, and Asymptotic Expansion of Nonlinear Filtering—0
Less is More: Towards Green Code Large Language Models via Unified Structural Pruning—0
Theory of Mixture-of-Experts for Mobile Edge Computing—0
DOLLAR: Few-Step Video Generation via Distillation and Latent Reward Optimization—0
Real-Time Tea Leaf Disease Detection Using Deep Learning-Based ModelsCode0
Adaptable and Precise: Enterprise-Scenario LLM Function-Calling Capability Training Pipeline—0
Optimization of Beyond Diagonal RIS: A Universal Framework Applicable to Arbitrary Architectures—0
A Computational Model of Learning and Memory Using Structurally Dynamic Cellular Automata—0
Consistent Human Image and Video Generation with Spatially Conditioned DiffusionCode0
Surrogate-assisted multi-objective design of complex multibody systems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified