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 3501–3525 of 4891 papers

TitleStatusHype
Long-Range LiDAR Vehicle Detection Through Clustering and Classification for Autonomous Racing—0
Long Sequence Modeling with Attention Tensorization: From Sequence to Tensor Learning—0
Long-term simulation of physical and mechanical behaviors using curriculum-transfer-learning based physics-informed neural networks—0
LongVQ: Long Sequence Modeling with Vector Quantization on Structured Memory—0
Look Locally Infer Globally: A Generalizable Face Anti-Spoofing Approach—0
Loosely Synchronized Search for Multi-agent Path Finding with Asynchronous Actions—0
LORTSAR: Low-Rank Transformer for Skeleton-based Action Recognition—0
Loss Functions in Deep Learning: A Comprehensive Review—0
Lost in OCR Translation? Vision-Based Approaches to Robust Document Retrieval—0
Low-Carbon Economic Dispatch of Bulk Power Systems Using Nash Bargaining Game—0
Low Compute and Fully Parallel Computer Vision With HashMatch—0
Enhanced Low-Dose CT Image Reconstruction by Domain and Task Shifting Gaussian Denoisers—0
Low-Dose CT Using Denoising Diffusion Probabilistic Model for 20 Speedup—0
Low-Rank Contextual Reinforcement Learning from Heterogeneous Human Feedback—0
Low-Rank Matrix Regression via Least-Angle Regression—0
Low-Rank Training of Deep Neural Networks for Emerging Memory Technology—0
Low Rank Training of Deep Neural Networks for Emerging Memory Technology—0
Low-Resolution Neural Networks—0
Low Resource Quadratic Forms for Knowledge Graph Embeddings—0
Low-variance estimation in the Plackett-Luce model via quasi-Monte Carlo sampling—0
L*ReLU: Piece-wise Linear Activation Functions for Deep Fine-grained Visual Categorization—0
LSDAT: Low-Rank and Sparse Decomposition for Decision-based Adversarial Attack—0
L-SR1 Adaptive Regularization by Cubics for Deep Learning—0
LSTM-based model predictive control with discrete inputs for irrigation scheduling—0
LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified