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 711–720 of 4891 papers

TitleStatusHype
Scalable Global Solution Techniques for High-Dimensional Models in Dynare—0
Automated Tomato Maturity Estimation Using an Optimized Residual Model with Pruning and Quantization Techniques—0
Evaluating a Novel Neuroevolution and Neural Architecture Search System—0
Sparse Dictionary Learning for Image Recovery by Iterative Shrinkage—0
Lightweight Models for Emotional Analysis in VideoCode0
HyperArm Bandit Optimization: A Novel approach to Hyperparameter Optimization and an Analysis of Bandit Algorithms in Stochastic and Adversarial Settings—0
Towards Efficient Large Scale Spatial-Temporal Time Series Forecasting via Improved Inverted Transformers—0
Multi-Modal Mamba Modeling for Survival Prediction (M4Survive): Adapting Joint Foundation Model RepresentationsCode2
RoMA: Scaling up Mamba-based Foundation Models for Remote SensingCode2
LVAgent: Long Video Understanding by Multi-Round Dynamical Collaboration of MLLM Agents—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified