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 1651–1675 of 4891 papers

TitleStatusHype
CrowdSplat: Exploring Gaussian Splatting For Crowd RenderingCode0
Contextual Reinforcement in Multimodal Token Compression for Large Language Models—0
FlexMotion: Lightweight, Physics-Aware, and Controllable Human Motion Generation—0
ITVTON:Virtual Try-On Diffusion Transformer Model Based on Integrated Image and Text—0
Federated Learning for Efficient Condition Monitoring and Anomaly Detection in Industrial Cyber-Physical Systems—0
Efficient Knowledge Distillation of SAM for Medical Image Segmentation—0
SSF-PAN: Semantic Scene Flow-Based Perception for Autonomous Navigation in Traffic Scenarios—0
HD-CB: The First Exploration of Hyperdimensional Computing for Contextual Bandits Problems—0
Deep-and-Wide Learning: Enhancing Data-Driven Inference via Synergistic Learning of Inter- and Intra-Data Representations—0
Stiff Transfer Learning for Physics-Informed Neural Networks—0
Radiance Surfaces: Optimizing Surface Representations with a 5D Radiance Field Loss—0
Evaluating Data Influence in Meta Learning—0
Real-Time Brain Tumor Detection in Intraoperative Ultrasound Using YOLO11: From Model Training to Deployment in the Operating RoomCode0
Gaussian credible intervals in Bayesian nonparametric estimation of the unseen—0
Directing Mamba to Complex Textures: An Efficient Texture-Aware State Space Model for Image Restoration—0
Lightweight Weighted Average Ensemble Model for Pneumonia Detection in Chest X-Ray Images—0
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
AI-Driven Secure Data Sharing: A Trustworthy and Privacy-Preserving Approach—0
Semantic Layered Embedding Diffusion in Large Language Models for Multi-Contextual Consistency—0
ReInc: Scaling Training of Dynamic Graph Neural Networks—0
Efficient and Interpretable Neural Networks Using Complex Lehmer Transform—0
Split-Merge: A Difference-based Approach for Dominant Eigenvalue Problem—0
DER Hosting capacity for distribution networks: definitions, attributes, use-cases and challenges—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified