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 3751–3775 of 4891 papers

TitleStatusHype
Benchmarking Data Efficiency and Computational Efficiency of Temporal Action Localization Models—0
Benchmarking Federated Machine Unlearning methods for Tabular Data—0
Benchmarking Large Language Models with Integer Sequence Generation Tasks—0
Benchmarking of CPU-intensive Stream Data Processing in The Edge Computing Systems—0
Benchmarking quantized LLaMa-based models on the Brazilian Secondary School Exam—0
Benchmarking real-time algorithms for in-phase auditory stimulation of low amplitude slow waves with wearable EEG devices during sleep—0
Benchmarking the human brain against computational architectures—0
Benchmarking Video Frame Interpolation—0
Best Arm Identification in Stochastic Bandits: Beyond β-optimality—0
Best-Subset Selection in Generalized Linear Models: A Fast and Consistent Algorithm via Splicing Technique—0
Beyond Attention: Learning Spatio-Temporal Dynamics with Emergent Interpretable Topologies—0
Beyond Frameworks: Unpacking Collaboration Strategies in Multi-Agent Systems—0
Beyond Reproducibility: Advancing Zero-shot LLM Reranking Efficiency with Setwise Insertion—0
Beyond Sentence-Level End-to-End Speech Translation: Context Helps—0
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction—0
Beyond Standard MoE: Mixture of Latent Experts for Resource-Efficient Language Models—0
Beyond the model: Key differentiators in large language models and multi-agent services—0
Activation-wise Propagation: A Universal Strategy to Break Timestep Constraints in Spiking Neural Networks for 3D Data Processing—0
Beyond Traditional Beamforming: Singular Vector Projection for MU-MIMO—0
Beyond Training: Dynamic Token Merging for Zero-Shot Video Understanding—0
Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs—0
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling—0
Bidirectional Long-Range Parser for Sequential Data Understanding—0
A High-Performance Object Proposals based on Horizontal High Frequency Signal—0
Bi-l0-l2-Norm Regularization for Blind Motion Deblurring—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified