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 111–120 of 4891 papers

TitleStatusHype
BEBLID: Boosted efficient binary local image descriptorCode2
Agent Attention: On the Integration of Softmax and Linear AttentionCode2
I^2-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene ForecastingCode2
AlphaNet: Scaling Up Local-frame-based Atomistic Interatomic PotentialCode2
HeadInfer: Memory-Efficient LLM Inference by Head-wise OffloadingCode2
2DMamba: Efficient State Space Model for Image Representation with Applications on Giga-Pixel Whole Slide Image ClassificationCode2
Grappa -- A Machine Learned Molecular Mechanics Force FieldCode2
Harder Tasks Need More Experts: Dynamic Routing in MoE ModelsCode2
Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence ModelingCode2
LeYOLO, New Scalable and Efficient CNN Architecture for Object DetectionCode2
Show:102550
← PrevPage 12 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified