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 691–700 of 4891 papers

TitleStatusHype
Towards Better Sample Efficiency in Multi-Agent Reinforcement Learning via Exploration—0
GFSNetwork: Differentiable Feature Selection via Gumbel-Sigmoid RelaxationCode0
Unlock Pose Diversity: Accurate and Efficient Implicit Keypoint-based Spatiotemporal Diffusion for Audio-driven Talking PortraitCode3
A new graph-based surrogate model for rapid prediction of crashworthiness performance of vehicle panel components—0
Personalize Anything for Free with Diffusion Transformer—0
Data-Driven Approximation of Binary-State Network Reliability Function: Algorithm Selection and Reliability Thresholds for Large-Scale Systems—0
GS-I^3: Gaussian Splatting for Surface Reconstruction from Illumination-Inconsistent ImagesCode1
AI-Powered Automated Model Construction for Patient-Specific CFD Simulations of Aortic Flows—0
Applications of Large Language Model Reasoning in Feature Generation—0
3D Gaussian Splatting against Moving Objects for High-Fidelity Street Scene ReconstructionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified