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 1576–1600 of 4891 papers

TitleStatusHype
Provably Efficient RLHF Pipeline: A Unified View from Contextual Bandits—0
Hierarchical Document Parsing via Large Margin Feature Matching and HeuristicsCode0
Long-term simulation of physical and mechanical behaviors using curriculum-transfer-learning based physics-informed neural networks—0
Mixed Integer Linear Programming for Active Contact Selection in Deep Brain Stimulation—0
Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive ForecastingCode0
MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition—0
Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity—0
Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface MeshesCode0
FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data—0
Smell of Source: Learning-Based Odor Source Localization with Molecular Communication—0
Bayesian Optimization by Kernel Regression and Density-based Exploration—0
Inventory Consensus Control in Supply Chain Networks using Dissipativity-Based Control and Topology Co-Design—0
Latent Convergence Modulation in Large Language Models: A Novel Approach to Iterative Contextual Realignment—0
Kolmogorov-Arnold Fourier Networks—0
Hierarchical Lexical Manifold Projection in Large Language Models: A Novel Mechanism for Multi-Scale Semantic Representation—0
CluStRE: Streaming Graph Clustering with Multi-Stage Refinement—0
Federated Learning with Reservoir State Analysis for Time Series Anomaly DetectionCode0
Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning—0
Graph Neural Network Enabled Pinching Antennas—0
Hybrid machine learning based scale bridging framework for permeability prediction of fibrous structures—0
Native Fortran Implementation of TensorFlow-Trained Deep and Bayesian Neural NetworksCode0
Tighter sparse variational Gaussian processes—0
Flopping for FLOPs: Leveraging equivariance for computational efficiency—0
Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient—0
TQ-DiT: Efficient Time-Aware Quantization for Diffusion Transformers—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified