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

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Showing 241–250 of 4891 papers

TitleStatusHype
Birdie: Advancing State Space Models with Reward-Driven Objectives and CurriculaCode1
Enhancing Medical Image Registration via Appearance Adjustment NetworksCode1
Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNNCode1
Benchmarking the Robustness of Spatial-Temporal Models Against CorruptionsCode1
Efficient Real-time Path Planning with Self-evolving Particle Swarm Optimization in Dynamic ScenariosCode1
Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context LearningCode1
BUFFER: Balancing Accuracy, Efficiency, and Generalizability in Point Cloud RegistrationCode1
Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated UncertaintyCode1
EViT: An Eagle Vision Transformer with Bi-Fovea Self-AttentionCode1
Energy-based physics-informed neural network for frictionless contact problems under large deformationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified