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

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Showing 1–10 of 4891 papers

TitleStatusHype
A Framework for Waterfall Pricing Using Simulation-Based Uncertainty Modeling—0
Computational-Statistical Tradeoffs from NP-hardness—0
Fremer: Lightweight and Effective Frequency Transformer for Workload Forecasting in Cloud Services—0
From Roots to Rewards: Dynamic Tree Reasoning with RLCode0
Heat Kernel Goes Topological—0
FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scaleCode3
FORTRESS: Function-composition Optimized Real-Time Resilient Structural Segmentation via Kolmogorov-Arnold Enhanced Spatial Attention NetworksCode0
Canonical Bayesian Linear System Identification—0
DCR: Quantifying Data Contamination in LLMs EvaluationCode0
Recursive Bound-Constrained AdaGrad with Applications to Multilevel and Domain Decomposition Minimization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified