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 1581–1590 of 4891 papers

TitleStatusHype
Provably Efficient RLHF Pipeline: A Unified View from Contextual Bandits—0
Long-term simulation of physical and mechanical behaviors using curriculum-transfer-learning based physics-informed neural networks—0
MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition—0
Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive ForecastingCode0
Inventory Consensus Control in Supply Chain Networks using Dissipativity-Based Control and Topology Co-Design—0
Bayesian Optimization by Kernel Regression and Density-based Exploration—0
Latent Convergence Modulation in Large Language Models: A Novel Approach to Iterative Contextual Realignment—0
Smell of Source: Learning-Based Odor Source Localization with Molecular Communication—0
Kolmogorov-Arnold Fourier Networks—0
CluStRE: Streaming Graph Clustering with Multi-Stage Refinement—0
Show:102550
← PrevPage 159 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified