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 1261–1270 of 4891 papers

TitleStatusHype
REJEPA: A Novel Joint-Embedding Predictive Architecture for Efficient Remote Sensing Image Retrieval—0
On the Connection Between Diffusion Models and Molecular Dynamics—0
Electromyography-Based Gesture Recognition: Hierarchical Feature Extraction for Enhanced Spatial-Temporal Dynamics—0
DP-LET: An Efficient Spatio-Temporal Network Traffic Prediction Framework—0
Integrating Identity-Based Identification against Adaptive Adversaries in Federated Learning—0
Advancing Semantic Caching for LLMs with Domain-Specific Embeddings and Synthetic Data—0
Towards Assessing Deep Learning Test Input Generators—0
Analytical Discovery of Manifold with Machine Learning—0
A Sensorimotor Vision Transformer—0
Improving Harmful Text Detection with Joint Retrieval and External Knowledge—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified