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 2251–2260 of 4891 papers

TitleStatusHype
Data-driven Modeling of Linearizable Power Flow for Large-scale Grid Topology Optimization—0
TACO-RL: Task Aware Prompt Compression Optimization with Reinforcement Learning—0
Deep Transfer Hashing for Adaptive Learning on Federated Streaming Data—0
Applications of Knowledge Distillation in Remote Sensing: A Survey—0
Memory Networks: Towards Fully Biologically Plausible Learning—0
Optimal Control for Discrete-Time Systems under Bounded Disturbances—0
Recurrent Interpolants for Probabilistic Time Series Prediction—0
SPRMamba: Surgical Phase Recognition for Endoscopic Submucosal Dissection with MambaCode0
On Vision Transformers for Classification Tasks in Side-Scan Sonar Imagery—0
Axial Attention Transformer Networks: A New Frontier in Breast Cancer Detection—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified