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 1841–1850 of 4891 papers

TitleStatusHype
Efficient Budget Allocation for Large-Scale LLM-Enabled Virtual Screening—0
ELASTIC: Efficient Linear Attention for Sequential Interest Compression—0
CTR-KAN: KAN for Adaptive High-Order Feature Interaction ModelingCode0
Bee-yond the Plateau: Training QNNs with Swarm Algorithms—0
SpectralEarth: Training Hyperspectral Foundation Models at ScaleCode1
ColorMamba: Towards High-quality NIR-to-RGB Spectral Translation with MambaCode0
MobileMEF: Fast and Efficient Method for Multi-Exposure FusionCode1
FlashGS: Efficient 3D Gaussian Splatting for Large-scale and High-resolution RenderingCode3
H_2-optimal Model Reduction of Linear Quadratic Output Systems in Finite Frequency Range—0
MetaSeg: MetaFormer-based Global Contexts-aware Network for Efficient Semantic SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified