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 2731–2740 of 4891 papers

TitleStatusHype
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model TrainingCode1
Randomized Dimension Reduction with Statistical Guarantees—0
Robustifying State-space Models for Long Sequences via Approximate Diagonalization—0
Variance-Aware Regret Bounds for Stochastic Contextual Dueling BanditsCode0
CoDBench: A Critical Evaluation of Data-driven Models for Continuous Dynamical Systems—0
Iterative Semi-Supervised Learning for Abdominal Organs and Tumor SegmentationCode0
Efficient MPC for Emergency Evasive Maneuvers, Part I: Hybridization of the Nonlinear Problem—0
Efficient MPC for Emergency Evasive Maneuvers, Part II: Comparative Assessment for Hybrid Control—0
Adaptive-Solver Framework for Dynamic Strategy Selection in Large Language Model ReasoningCode0
Quantum-Based Feature Selection for Multi-classification Problem in Complex Systems with Edge Computing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified