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 1191–1200 of 4891 papers

TitleStatusHype
Quantum framework for Reinforcement Learning: Integrating Markov decision process, quantum arithmetic, and trajectory search—0
Exact Acceleration of Subgraph Graph Neural Networks by Eliminating Computation Redundancy—0
Underwater Image Restoration via Polymorphic Large Kernel CNNsCode1
ArchComplete: Autoregressive 3D Architectural Design Generation with Hierarchical Diffusion-Based UpsamplingCode0
Edge-AI for Agriculture: Lightweight Vision Models for Disease Detection in Resource-Limited Settings—0
An efficient search-and-score algorithm for ancestral graphs using multivariate information scores—0
Coupled differential-algebraic equations framework for modeling six-degree-of-freedom flight dynamics of asymmetric fixed-wing aircraft—0
DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image ClassificationCode0
Assessing Human Editing Effort on LLM-Generated Texts via Compression-Based Edit DistanceCode0
GausSim: Foreseeing Reality by Gaussian Simulator for Elastic Objects—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified