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

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Showing 1011–1020 of 4891 papers

TitleStatusHype
Directing Mamba to Complex Textures: An Efficient Texture-Aware State Space Model for Image Restoration—0
Real-Time Brain Tumor Detection in Intraoperative Ultrasound Using YOLO11: From Model Training to Deployment in the Operating RoomCode0
Evaluating Data Influence in Meta Learning—0
Mixture-of-Mamba: Enhancing Multi-Modal State-Space Models with Modality-Aware SparsityCode2
Lightweight Weighted Average Ensemble Model for Pneumonia Detection in Chest X-Ray Images—0
Gaussian credible intervals in Bayesian nonparametric estimation of the unseen—0
Return of the Encoder: Maximizing Parameter Efficiency for SLMsCode1
ARFlow: Autogressive Flow with Hybrid Linear Attention—0
Guaranteed Multidimensional Time Series Prediction via Deterministic Tensor Completion TheoryCode0
Quantum-Enhanced Attention Mechanism in NLP: A Hybrid Classical-Quantum Approach—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified