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 2001–2025 of 4891 papers

TitleStatusHype
FGP: Feature-Gradient-Prune for Efficient Convolutional Layer PruningCode0
High-Throughput Blind Co-Channel Interference Cancellation for Edge Devices Using Depthwise Separable Convolutions, Quantization, and Pruning—0
S3TU-Net: Structured Convolution and Superpixel Transformer for Lung Nodule Segmentation—0
Data-to-Model Distillation: Data-Efficient Learning FrameworkCode0
SynCoTrain: A Dual Classifier PU-learning Framework for Synthesizability Prediction—0
MoE-Lightning: High-Throughput MoE Inference on Memory-constrained GPUs—0
Integrating and Comparing Radiality Constraints for Optimized Distribution System Reconfiguration—0
Robust and Constrained Estimation of State-Space Models: A Majorization-Minimization Approach—0
EROAM: Event-based Camera Rotational Odometry and Mapping in Real-time—0
SEFD: Semantic-Enhanced Framework for Detecting LLM-Generated TextCode0
TSFormer: A Robust Framework for Efficient UHD Image Restoration—0
LoRA Unlearns More and Retains More (Student Abstract)Code0
STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing—0
Y-MAP-Net: Real-time depth, normals, segmentation, multi-label captioning and 2D human pose in RGB images—0
DiffFNO: Diffusion Fourier Neural Operator—0
A Secure Estimator with Gaussian Bernoulli Mixture Model—0
Neural Graph Simulator for Complex Systems—0
Advancing Diffusion Models: Alias-Free Resampling and Enhanced Rotational Equivariance—0
The Good, The Efficient and the Inductive Biases: Exploring Efficiency in Deep Learning Through the Use of Inductive Biases—0
Cross Space and Time: A Spatio-Temporal Unitized Model for Traffic Flow Forecasting—0
When Mamba Meets xLSTM: An Efficient and Precise Method with the xLSTM-VMUNet Model for Skin lesion SegmentationCode0
Clustered Patch Embeddings for Permutation-Invariant Classification of Whole Slide Images—0
DBgDel: Database-Enhanced Gene Deletion Framework for Growth-Coupled Production in Genome-Scale Metabolic ModelsCode0
Shallow Signed Distance Functions for Kinematic Collision Bodies—0
HeteroSample: Meta-path Guided Sampling for Heterogeneous Graph Representation Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified