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

Showing 241250 of 4891 papers

TitleStatusHype
SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point CloudsCode1
PATS: Process-Level Adaptive Thinking Mode SwitchingCode1
LIMOPro: Reasoning Refinement for Efficient and Effective Test-time ScalingCode1
RealEngine: Simulating Autonomous Driving in Realistic ContextCode1
MGStream: Motion-aware 3D Gaussian for Streamable Dynamic Scene ReconstructionCode1
Occult: Optimizing Collaborative Communication across Experts for Accelerated Parallel MoE Training and InferenceCode1
DragLoRA: Online Optimization of LoRA Adapters for Drag-based Image Editing in Diffusion ModelCode1
SepPrune: Structured Pruning for Efficient Deep Speech SeparationCode1
Self-Learning Hyperspectral and Multispectral Image Fusion via Adaptive Residual Guided Subspace Diffusion ModelCode1
FilterTS: Comprehensive Frequency Filtering for Multivariate Time Series ForecastingCode1
Show:102550
← PrevPage 25 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified