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 81–90 of 4891 papers

TitleStatusHype
LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge DistillationCode3
Hybrid 3D-4D Gaussian Splatting for Fast Dynamic Scene RepresentationCode2
I^2-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene ForecastingCode2
Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence ModelingCode2
Advances in 4D Generation: A SurveyCode2
HeadInfer: Memory-Efficient LLM Inference by Head-wise OffloadingCode2
3D-RCNet: Learning from Transformer to Build a 3D Relational ConvNet for Hyperspectral Image ClassificationCode2
Agent Attention: On the Integration of Softmax and Linear AttentionCode2
Harder Tasks Need More Experts: Dynamic Routing in MoE ModelsCode2
InteractRank: Personalized Web-Scale Search Pre-Ranking with Cross Interaction FeaturesCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified