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 1081–1090 of 4891 papers

TitleStatusHype
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive UncertaintiesCode0
Global Safe Sequential Learning via Efficient Knowledge TransferCode0
Analyzing Large Language Models for Classroom Discussion AssessmentCode0
GFSNetwork: Differentiable Feature Selection via Gumbel-Sigmoid RelaxationCode0
Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry DetectionCode0
Geoseg: A Computer Vision Package for Automatic Building Segmentation and Outline ExtractionCode0
Beyond Prediction: On-street Parking Recommendation using Heterogeneous Graph-based List-wise RankingCode0
CTR-KAN: KAN for Adaptive High-Order Feature Interaction ModelingCode0
Scalable Exploration via Ensemble++Code0
Beyond Attentive Tokens: Incorporating Token Importance and Diversity for Efficient Vision TransformersCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified