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 1641–1650 of 4891 papers

TitleStatusHype
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM—0
Locality-aware Surrogates for Gradient-based Black-box Optimization—0
Contextually Structured Token Dependency Encoding for Large Language Models—0
Transfer Learning for Keypoint Detection in Low-Resolution Thermal TUG Test Images—0
LLM-Generated Heuristics for AI Planning: Do We Even Need Domain-Independence Anymore?—0
PDE-DKL: PDE-constrained deep kernel learning in high dimensionalityCode0
AlphaAdam:Asynchronous Masked Optimization with Dynamic Alpha for Selective UpdatesCode0
Model-Adaptive Approach to Dynamic Discrete Choice Models with Large State Spaces—0
A Hybrid Dynamic Subarray Architecture for Efficient DOA Estimation in THz Ultra-Massive Hybrid MIMO Systems—0
Action Recognition Using Temporal Shift Module and Ensemble LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified