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 1226–1250 of 4891 papers

TitleStatusHype
Successive Jump and Mode Decomposition—0
SAEs Can Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in LLMs—0
V2V3D: View-to-View Denoised 3D Reconstruction for Light-Field Microscopy—0
Probability Estimation and Scheduling Optimization for Battery Swap Stations via LRU-Enhanced Genetic Algorithm and Dual-Factor Decision SystemCode0
Cluster-Driven Expert Pruning for Mixture-of-Experts Large Language ModelsCode0
Search-contempt: a hybrid MCTS algorithm for training AlphaZero-like engines with better computational efficiency—0
STEI-PCN: an efficient pure convolutional network for traffic prediction via spatial-temporal encoding and inferring—0
Deep Reinforcement Learning for Day-to-day Dynamic Tolling in Tradable Credit Schemes—0
How to Detect and Defeat Molecular Mirage: A Metric-Driven Benchmark for Hallucination in LLM-based Molecular Comprehension—0
Gradient-based Sample Selection for Faster Bayesian Optimization—0
Representation Meets Optimization: Training PINNs and PIKANs for Gray-Box Discovery in Systems Pharmacology—0
A Comparison of Deep Learning Methods for Cell Detection in Digital CytologyCode0
Beyond Reproducibility: Advancing Zero-shot LLM Reranking Efficiency with Setwise Insertion—0
Adapting GT2-FLS for Uncertainty Quantification: A Blueprint Calibration StrategyCode0
Density Approximation of Affine Jump Diffusions via Closed-Form Moment Matching—0
Regret Bounds for Robust Online Decision Making—0
Distilling Textual Priors from LLM to Efficient Image FusionCode0
Optuna vs Code Llama: Are LLMs a New Paradigm for Hyperparameter Tuning?—0
econSG: Efficient and Multi-view Consistent Open-Vocabulary 3D Semantic Gaussians—0
Hybrid Temporal Differential Consistency Autoencoder for Efficient and Sustainable Anomaly Detection in Cyber-Physical Systems—0
WoundAmbit: Bridging State-of-the-Art Semantic Segmentation and Real-World Wound Care—0
Sparse Optimization for Transfer Learning: A L0-Regularized Framework for Multi-Source Domain Adaptation—0
Constrained Gaussian Process Motion Planning via Stein Variational Newton Inference—0
Federated Learning for Medical Image Classification: A Comprehensive Benchmark—0
Neural network-enhanced integrators for simulating ordinary differential equations—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified