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 271–280 of 4891 papers

TitleStatusHype
DragLoRA: Online Optimization of LoRA Adapters for Drag-based Image Editing in Diffusion ModelCode1
Structureless VIO—0
Beyond Frameworks: Unpacking Collaboration Strategies in Multi-Agent Systems—0
Llama-Affinity: A Predictive Antibody Antigen Binding Model Integrating Antibody Sequences with Llama3 Backbone Architecture—0
Multi-Order Wavelet Derivative Transform for Deep Time Series Forecasting—0
Modèles de Substitution pour les Modèles à base d'Agents : Enjeux, Méthodes et ApplicationsCode0
Self-Learning Hyperspectral and Multispectral Image Fusion via Adaptive Residual Guided Subspace Diffusion ModelCode1
SepPrune: Structured Pruning for Efficient Deep Speech SeparationCode1
whittlehurst: A Python package implementing Whittle's likelihood estimation of the Hurst exponent—0
Simple and Effective Specialized Representations for Fair Classifiers—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified