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 1031–1040 of 4891 papers

TitleStatusHype
Structureless VIO—0
Modèles de Substitution pour les Modèles à base d'Agents : Enjeux, Méthodes et ApplicationsCode0
Multi-Order Wavelet Derivative Transform for Deep Time Series Forecasting—0
Llama-Affinity: A Predictive Antibody Antigen Binding Model Integrating Antibody Sequences with Llama3 Backbone Architecture—0
Neural-Inspired Advances in Integral Cryptanalysis—0
whittlehurst: A Python package implementing Whittle's likelihood estimation of the Hurst exponent—0
Simple and Effective Specialized Representations for Fair Classifiers—0
IISE PG&E Energy Analytics Challenge 2025: Hourly-Binned Regression Models Beat Transformers in Load Forecasting—0
Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach—0
LGBQPC: Local Granular-Ball Quality Peaks Clustering—0
Show:102550
← PrevPage 104 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified