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 2126–2150 of 4891 papers

TitleStatusHype
Dendritic Computing with Multi-Gate Ferroelectric Field-Effect Transistors—0
Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation—0
Attentive cross-modal paratope prediction—0
Algorithm Unrolling for Massive Access via Deep Neural Network with Theoretical Guarantee—0
DELTA: Decomposed Efficient Long-Term Robot Task Planning using Large Language Models—0
DehazeGS: Seeing Through Fog with 3D Gaussian Splatting—0
Algorithms of Real-Time Navigation and Control of Autonomous Unmanned Vehicles—0
Diffusion Models, Image Super-Resolution And Everything: A Survey—0
DeGraF-Flow: Extending DeGraF Features for accurate and efficient sparse-to-dense optical flow estimation—0
Attention Is Not Always the Answer: Optimizing Voice Activity Detection with Simple Feature Fusion—0
Deformable Capsules for Object Detection—0
DefMamba: Deformable Visual State Space Model—0
Attention is Naturally Sparse with Gaussian Distributed Input—0
Higher Order Transformers: Efficient Attention Mechanism for Tensor Structured Data—0
Defect Transformer: An Efficient Hybrid Transformer Architecture for Surface Defect Detection—0
Defect Localization Using Region of Interest and Histogram-Based Enhancement Approaches in 3D-Printing—0
Defect detection for patterned fabric images based on GHOG and low-rank decomposition—0
Accelerated Fully First-Order Methods for Bilevel and Minimax Optimization—0
High Energy Density Radiative Transfer in the Diffusion Regime with Fourier Neural Operators—0
Deep vs. Diverse Architectures for Classification Problems—0
DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutions—0
Attention-Driven Hierarchical Reinforcement Learning with Particle Filtering for Source Localization in Dynamic Fields—0
Deep Video Demoireing via Compact Invertible Dyadic Decomposition—0
Deep Unsupervised Hashing by Distilled Smooth Guidance—0
Algebraic-Combinatorial Methods for Low-Rank Matrix Completion with Application to Athletic Performance Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified