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 911–920 of 4891 papers

TitleStatusHype
Vid2Sim: Generalizable, Video-based Reconstruction of Appearance, Geometry and Physics for Mesh-free Simulation—0
Unlocking Chemical Insights: Superior Molecular Representations from Intermediate Encoder LayersCode0
DynamicMind: A Tri-Mode Thinking System for Large Language Models—0
Efficient Robust Conformal Prediction via Lipschitz-Bounded NetworksCode0
U-NetMN and SegNetMN: Modified U-Net and SegNet models for bimodal SAR image segmentation—0
TALL -- A Trainable Architecture for Enhancing LLM Performance in Low-Resource Languages—0
A Survey on Vietnamese Document Analysis and Recognition: Challenges and Future Directions—0
SF^2Bench: Evaluating Data-Driven Models for Compound Flood Forecasting in South Florida—0
GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money LaunderingCode0
Pruning Everything, Everywhere, All at OnceCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified