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 426–450 of 4891 papers

TitleStatusHype
SUPRA: Subspace Parameterized Attention for Neural Operator on General Domains—0
A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained SettingsCode0
Simulating biochemical reactions: The Linear Noise Approximation can capture non-linear dynamics—0
Feature Selection via GANs (GANFS): Enhancing Machine Learning Models for DDoS Mitigation—0
Enhanced Data-driven Topology Design Methodology with Multi-level Mesh and Correlation-based Mutation for Stress-related Multi-objective Optimization—0
Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive SurveyCode2
DistilQwen2.5: Industrial Practices of Training Distilled Open Lightweight Language Models—0
When Cloud Removal Meets Diffusion Model in Remote Sensing—0
Exploring _0 Sparsification for Inference-free Sparse RetrieversCode1
Neural ATTF: A Scalable Solution to Lifelong Multi-Agent Path Planning—0
STARS: Sparse Learning Correlation Filter with Spatio-temporal Regularization and Super-resolution Reconstruction for Thermal Infrared Target Tracking—0
SMTT: Novel Structured Multi-task Tracking with Graph-Regularized Sparse Representation for Robust Thermal Infrared Target Tracking—0
ReasoningV: Efficient Verilog Code Generation with Adaptive Hybrid Reasoning ModelCode0
VM-BHINet:Vision Mamba Bimanual Hand Interaction Network for 3D Interacting Hand Mesh Recovery From a Single RGB Image—0
Mixed-Precision Conjugate Gradient Solvers with RL-Driven Precision Tuning—0
Quantum-Enhanced Reinforcement Learning for Power Grid Security Assessment—0
Efficient Spiking Point Mamba for Point Cloud Analysis—0
Segment Any Crack: Deep Semantic Segmentation Adaptation for Crack Detection—0
RAMCT: Novel Region-adaptive Multi-channel Tracker with Iterative Tikhonov Regularization for Thermal Infrared Tracking—0
Optimal Lattice Boltzmann Closures through Multi-Agent Reinforcement Learning—0
Segregation and Context Aggregation Network for Real-time Cloud Segmentation—0
CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive SurveyCode2
Latent Tensor Factorization with Nonlinear PID Control for Missing Data Recovery in Non-Intrusive Load Monitoring—0
Science Hierarchography: Hierarchical Organization of Science LiteratureCode0
MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified