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 1151–1175 of 4891 papers

TitleStatusHype
PODNO: Proper Orthogonal Decomposition Neural Operators—0
On the workflow, opportunities and challenges of developing foundation model in geophysics—0
Precision Neural Network Quantization via Learnable Adaptive Modules—0
Combining GCN Structural Learning with LLM Chemical Knowledge for or Enhanced Virtual Screening—0
Mixed Bernstein-Fourier Approximants for Optimal Trajectory Generation with Periodic Behavior—0
Towards Robust LLMs: an Adversarial Robustness Measurement FrameworkCode0
Data-Driven Surrogate Modeling Techniques to Predict the Effective Contact Area of Rough Surface Contact Problems—0
A Spatially-Aware Multiple Instance Learning Framework for Digital PathologyCode0
Hyper-Transforming Latent Diffusion Models—0
Improving Significant Wave Height Prediction Using Chronos Models—0
An Accelerated Camera 3DMA Framework for Efficient Urban GNSS Multipath Estimation—0
LLMs meet Federated Learning for Scalable and Secure IoT Management—0
SUPRA: Subspace Parameterized Attention for Neural Operator on General Domains—0
Probabilistic Emulation of the Community Radiative Transfer Model Using Machine Learning—0
Research on Cloud Platform Network Traffic Monitoring and Anomaly Detection System based on Large Language Models—0
A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained SettingsCode0
Observability conditions for neural state-space models with eigenvalues and their roots of unity—0
ScaleGNN: Towards Scalable Graph Neural Networks via Adaptive High-order Neighboring Feature Fusion—0
Enhanced Data-driven Topology Design Methodology with Multi-level Mesh and Correlation-based Mutation for Stress-related Multi-objective Optimization—0
Simulating biochemical reactions: The Linear Noise Approximation can capture non-linear dynamics—0
Neural ATTF: A Scalable Solution to Lifelong Multi-Agent Path Planning—0
Feature Selection via GANs (GANFS): Enhancing Machine Learning Models for DDoS Mitigation—0
When Cloud Removal Meets Diffusion Model in Remote Sensing—0
DistilQwen2.5: Industrial Practices of Training Distilled Open Lightweight Language Models—0
STARS: Sparse Learning Correlation Filter with Spatio-temporal Regularization and Super-resolution Reconstruction for Thermal Infrared Target Tracking—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified