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 2801–2825 of 4891 papers

TitleStatusHype
Global Safe Sequential Learning via Efficient Knowledge TransferCode0
A Self-supervised Pressure Map human keypoint Detection Approch: Optimizing Generalization and Computational Efficiency Across Datasets—0
Learning Dual-arm Object Rearrangement for Cartesian Robots—0
Improving Building Temperature Forecasting: A Data-driven Approach with System Scenario Clustering—0
Tumor segmentation on whole slide images: training or prompting?—0
EffLoc: Lightweight Vision Transformer for Efficient 6-DOF Camera Relocalization—0
FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML—0
DB-LLM: Accurate Dual-Binarization for Efficient LLMs—0
Flexible Robust Optimal Bidding of Renewable Virtual Power Plants in Sequential MarketsCode0
DualView: Data Attribution from the Dual PerspectiveCode0
Network Inversion of Binarised Neural Nets—0
Emulating the interstellar medium chemistry with neural operators—0
Random Projection Neural Networks of Best Approximation: Convergence theory and practical applications—0
PhaseEvo: Towards Unified In-Context Prompt Optimization for Large Language Models—0
Turn Waste into Worth: Rectifying Top-k Router of MoE—0
Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank BanditsCode0
Collaborative Learning with Different Labeling Functions—0
Generalizability of Mixture of Domain-Specific Adapters from the Lens of Signed Weight Directions and its Application to Effective Model Pruning—0
Private PAC Learning May be Harder than Online Learning—0
Closed-form Filtering for Non-linear Systems—0
Multi-Fidelity Methods for Optimization: A Survey—0
Exploiting Estimation Bias in Clipped Double Q-Learning for Continous Control Reinforcement Learning Tasks—0
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional SystemsCode0
Oracle-Efficient Differentially Private Learning with Public Data—0
Accelerating Distributed Deep Learning using Lossless Homomorphic CompressionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified