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 141–150 of 4891 papers

TitleStatusHype
BiFormer: Vision Transformer with Bi-Level Routing AttentionCode2
HeadInfer: Memory-Efficient LLM Inference by Head-wise OffloadingCode2
I^2-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene ForecastingCode2
LightGNN: Simple Graph Neural Network for RecommendationCode2
BEBLID: Boosted efficient binary local image descriptorCode2
GotenNet: Rethinking Efficient 3D Equivariant Graph Neural NetworksCode2
Geometry Aware Operator Transformer as an Efficient and Accurate Neural Surrogate for PDEs on Arbitrary DomainsCode2
Advances in 4D Generation: A SurveyCode2
GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-MeshCode2
Free Video-LLM: Prompt-guided Visual Perception for Efficient Training-free Video LLMsCode2
Show:102550
← PrevPage 15 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified