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 2181–2190 of 4891 papers

TitleStatusHype
Quantum-Inspired Portfolio Optimization In The QUBO Framework—0
IGroupSS-Mamba: Interval Group Spatial-Spectral Mamba for Hyperspectral Image Classification—0
SegINR: Segment-wise Implicit Neural Representation for Sequence Alignment in Neural Text-to-Speech—0
SPikE-SSM: A Sparse, Precise, and Efficient Spiking State Space Model for Long Sequences Learning—0
Diffusion Models in 3D Vision: A Survey—0
Granular Ball Twin Support Vector MachineCode0
CR-CTC: Consistency regularization on CTC for improved speech recognition—0
GARLIC: LLM-Guided Dynamic Progress Control with Hierarchical Weighted Graph for Long Document QA—0
Upsample or Upweight? Balanced Training on Heavily Imbalanced Datasets—0
Bisimulation metric for Model Predictive ControlCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified