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 1701–1750 of 4891 papers

TitleStatusHype
Question-to-Question Retrieval for Hallucination-Free Knowledge Access: An Approach for Wikipedia and Wikidata Question Answering—0
GCSAM: Gradient Centralized Sharpness Aware MinimizationCode0
Sparse L0-norm based Kernel-free Quadratic Surface Support Vector MachinesCode0
Leveraging GANs For Active Appearance Models Optimized Model Fitting—0
Decomposing and Fusing Intra- and Inter-Sensor Spatio-Temporal Signal for Multi-Sensor Wearable Human Activity RecognitionCode0
Computational Discovery of Chiasmus in Ancient Religious TextCode0
HOPS: High-order Polynomials with Self-supervised Dimension Reduction for Load Forecasting—0
BOOST: Microgrid Sizing using Ordinal Optimization—0
Which price to pay? Auto-tuning building MPC controller for optimal economic cost—0
Recovering Unobserved Network Links from Aggregated Relational Data: Discussions on Bayesian Latent Surface Modeling and Penalized Regression—0
Revisiting Ensemble Methods for Stock Trading and Crypto Trading Tasks at ACM ICAIF FinRL Contest 2023-2024—0
Wasserstein Adaptive Value Estimation for Actor-Critic Reinforcement Learning—0
OMoE: Diversifying Mixture of Low-Rank Adaptation by Orthogonal Finetuning—0
Analytical Models of Frequency and Voltage in Large-Scale All-Inverter Power Systems—0
Adaptive Clustering for Efficient Phenotype Segmentation of UAV Hyperspectral Data—0
DPERC: Direct Parameter Estimation for Mixed Data—0
Deep Learning for Early Alzheimer Disease Detection with MRI ScansCode0
Parallel multi-objective metaheuristics for smart communications in vehicular networks—0
Graph Neural Networks for Travel Distance Estimation and Route Recommendation Under Probabilistic Hazards—0
Towards Lightweight and Stable Zero-shot TTS with Self-distilled Representation Disentanglement—0
Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography—0
Cancer-Net PCa-Seg: Benchmarking Deep Learning Models for Prostate Cancer Segmentation Using Synthetic Correlated Diffusion Imaging—0
LeMo: Enabling LEss Token Involvement for MOre Context Fine-tuning—0
AutoLoop: Fast Visual SLAM Fine-tuning through Agentic Curriculum Learning—0
Deep Learning Meets Queue-Reactive: A Framework for Realistic Limit Order Book Simulation—0
SPEQ: Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning—0
Learning Joint Denoising, Demosaicing, and Compression from the Raw Natural Image Noise DatasetCode0
Robust Hyperspectral Image Panshapring via Sparse Spatial-Spectral Representation—0
Optimizing Language Models for Grammatical Acceptability: A Comparative Study of Fine-Tuning Techniques—0
Black-box Optimization with Simultaneous Statistical Inference for Optimal Performance—0
Efficient and Accurate Full-Waveform Inversion with Total Variation ConstraintCode0
Economic Model Predictive Control for Periodic Operation: A Quadratic Programming Approach—0
A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation—0
Transforming Indoor Localization: Advanced Transformer Architecture for NLOS Dominated Wireless Environments with Distributed Sensors—0
An Enhanced Zeroth-Order Stochastic Frank-Wolfe Framework for Constrained Finite-Sum OptimizationCode0
UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTMCode0
QuantuneV2: Compiler-Based Local Metric-Driven Mixed Precision Quantization for Practical Embedded AI Applications—0
A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams—0
A Hybrid Framework for Reinsurance Optimization: Integrating Generative Models and Reinforcement LearningCode0
A Short-Term Predict-Then-Cluster Framework for Meal Delivery Services—0
GenMol: A Drug Discovery Generalist with Discrete Diffusion—0
Efficient Representations for High-Cardinality Categorical Variables in Machine Learning—0
Universal-2-TF: Robust All-Neural Text Formatting for ASR—0
Enhanced Quantile Regression with Spiking Neural Networks for Long-Term System Health Prognostics—0
On Computational Limits and Provably Efficient Criteria of Visual Autoregressive Models: A Fine-Grained Complexity Analysis—0
Color Correction Meets Cross-Spectral Refinement: A Distribution-Aware Diffusion for Underwater Image Restoration—0
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA—0
HyFusion: Enhanced Reception Field Transformer for Hyperspectral Image Fusion—0
CGP-Tuning: Structure-Aware Soft Prompt Tuning for Code Vulnerability Detection—0
SPAR3D: Stable Point-Aware Reconstruction of 3D Objects from Single Images—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified