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 2651–2660 of 4891 papers

TitleStatusHype
Saliency Driven Object recognition in egocentric videos with deep CNN—0
Samba-ASR: State-Of-The-Art Speech Recognition Leveraging Structured State-Space Models—0
Sample and Computationally Efficient Stochastic Kriging in High Dimensions—0
Efficient Budget Allocation for Large-Scale LLM-Enabled Virtual Screening—0
Sampling Constrained Continuous Probability Distributions: A Review—0
Sampling-guided Heterogeneous Graph Neural Network with Temporal Smoothing for Scalable Longitudinal Data Imputation—0
Sampling Strategies for Real-Time Action Recognition—0
Sampling Techniques for Streaming Cross Document Coreference Resolution—0
SAND: One-Shot Feature Selection with Additive Noise Distortion—0
SANN-PSZ: Spatially Adaptive Neural Network for Head-Tracked Personal Sound Zones—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified