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 3261–3270 of 4891 papers

TitleStatusHype
BEBERT: Efficient and Robust Binary Ensemble BERTCode0
Joint Semantic Transfer Network for IoT Intrusion Detection—0
Efficient and Effective Augmentation Strategy for Adversarial TrainingCode1
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows—0
Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception—0
SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain—0
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds—0
Delving into Masked Autoencoders for Multi-Label Thorax Disease ClassificationCode1
Joint Speech Translation and Named Entity Recognition—0
The mass-conversion method: a hybrid technique for simulating well-mixed chemical reaction networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified