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 3351–3375 of 4891 papers

TitleStatusHype
On the Trend-corrected Variant of Adaptive Stochastic Optimization Methods—0
Adaptable and Precise: Enterprise-Scenario LLM Function-Calling Capability Training Pipeline—0
Adapting Physics-Informed Neural Networks for Bifurcation Detection in Ecological Migration Models—0
Adaptive and oblivious statistical adversaries are equivalent—0
Adaptive Attention-Based Model for 5G Radio-based Outdoor Localization—0
Adaptive Audio-Visual Speech Recognition via Matryoshka-Based Multimodal LLMs—0
Adaptive Bayesian Optimization for High-Precision Motion Systems—0
Adaptive Clustering for Efficient Phenotype Segmentation of UAV Hyperspectral Data—0
Adaptive Conditional Expert Selection Network for Multi-domain Recommendation—0
Adaptive Cyclic Diffusion for Inference Scaling—0
Adaptive Deep Learning for Efficient Visual Pose Estimation aboard Ultra-low-power Nano-drones—0
Adaptive Direction-Guided Structure Tensor Total Variation—0
Adaptive Divergence-based Non-negative Latent Factor Analysis—0
Adaptive Extensive Cancellation Algorithm and Harmonic Enhanced Heart Rate Estimation based on MMWave Radar—0
Adaptive Few-Shot Learning PoC Ultrasound COVID-19 Diagnostic System—0
Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach—0
Adaptive Multi-resolution Hash-Encoding Framework for INR-based Dental CBCT Reconstruction with Truncated FOV—0
Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Training—0
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows—0
Adaptive Resolution Residual Networks -- Generalizing Across Resolutions Easily and Efficiently—0
Adaptive Sampling for Continuous Group Equivariant Neural Networks—0
Ada-SISE: Adaptive Semantic Input Sampling for Efficient Explanation of Convolutional Neural Networks—0
A Data-Driven Sparse Polynomial Chaos Expansion Method to Assess Probabilistic Total Transfer Capability for Power Systems with Renewables—0
A Dataset Fusion Algorithm for Generalised Anomaly Detection in Homogeneous Periodic Time Series Datasets—0
ADC/DAC-Free Analog Acceleration of Deep Neural Networks with Frequency Transformation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified