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 2251–2275 of 4891 papers

TitleStatusHype
Proof-of-Learning with Incentive Security—0
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image ClassificationCode1
Diffusion-Based Joint Temperature and Precipitation Emulation of Earth System Models—0
TSLANet: Rethinking Transformers for Time Series Representation LearningCode3
BERT-LSH: Reducing Absolute Compute For AttentionCode0
Minimax Optimal Goodness-of-Fit Testing with Kernel Stein Discrepancy—0
Generalized Population-Based Training for Hyperparameter Optimization in Reinforcement LearningCode0
Rethinking Transformer-Based Blind-Spot Network for Self-Supervised Image DenoisingCode2
Attention-Aware Laparoscopic Image Desmoking Network with Lightness Embedding and Hybrid Guided EmbeddingCode0
Precoder Design for User-Centric Network Massive MIMO with Matrix Manifold Optimization—0
GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-MeshCode2
Efficient Sound Field Reconstruction with Conditional Invertible Neural Networks—0
Adapting LLaMA Decoder to Vision TransformerCode1
Efficient Training of Probabilistic Neural Networks for Survival AnalysisCode0
Dimensionality Reduction in Sentence Transformer Vector Databases with Fast Fourier Transform—0
Bidirectional Long-Range Parser for Sequential Data Understanding—0
LHU-Net: A Light Hybrid U-Net for Cost-Efficient, High-Performance Volumetric Medical Image SegmentationCode2
GLCM-Based Feature Combination for Extraction Model Optimization in Object Detection Using Machine Learning—0
Reliable Feature Selection for Adversarially Robust Cyber-Attack Detection—0
Unlocking Parameter-Efficient Fine-Tuning for Low-Resource Language Translation—0
On the Efficiency of Convolutional Neural Networks—0
DELTA: Decomposed Efficient Long-Term Robot Task Planning using Large Language Models—0
Attention is Naturally Sparse with Gaussian Distributed Input—0
CATP: Cross-Attention Token Pruning for Accuracy Preserved Multimodal Model Inference—0
Improved model-free bounds for multi-asset options using option-implied information and deep learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified