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 3551–3575 of 4891 papers

TitleStatusHype
Mamba for Scalable and Efficient Personalized Recommendations—0
Mamba Hawkes Process—0
MambaLoc: Efficient Camera Localisation via State Space Model—0
MambaStyle: Efficient StyleGAN Inversion for Real Image Editing with State-Space Models—0
MapBERT: Bitwise Masked Modeling for Real-Time Semantic Mapping Generation—0
Mapping at First Sense: A Lightweight Neural Network-Based Indoor Structures Prediction Method for Robot Autonomous Exploration—0
Mastering the Digital Art of War: Developing Intelligent Combat Simulation Agents for Wargaming Using Hierarchical Reinforcement Learning—0
Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations—0
MATEY: multiscale adaptive foundation models for spatiotemporal physical systems—0
H_2-optimal Model Reduction of Linear Quadratic Output Systems in Finite Frequency Range—0
Mathematical Foundations of Graph-Based Bayesian Semi-Supervised Learning—0
Mathematical foundations of stable RKHSs—0
Mathematical Modeling of Option Pricing with an Extended Black-Scholes Framework—0
Matroid Bandits: Fast Combinatorial Optimization with Learning—0
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model—0
Maximal Volume Matrix Cross Approximation for Image Compression and Least Squares Solution—0
Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition—0
Maximum-Entropy Adversarial Audio Augmentation for Keyword Spotting—0
MC-CIM: Compute-in-Memory with Monte-Carlo Dropouts for Bayesian Edge Intelligence—0
MC-GRU:a Multi-Channel GRU network for generalized nonlinear structural response prediction across structures—0
MDFN: Multi-Scale Deep Feature Learning Network for Object Detection—0
Mean-Variance Efficient Collaborative Filtering for Stock Recommendation—0
Fast And Efficient Boolean Matrix Factorization By Geometric Segmentation—0
Efficient Automated Circuit Discovery in Transformers using Contextual Decomposition—0
Med-DANet V2: A Flexible Dynamic Architecture for Efficient Medical Volumetric Segmentation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified