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 351–375 of 4891 papers

TitleStatusHype
Adaptive Data Optimization: Dynamic Sample Selection with Scaling LawsCode1
BUFFER: Balancing Accuracy, Efficiency, and Generalizability in Point Cloud RegistrationCode1
Cached Multi-Lora Composition for Multi-Concept Image GenerationCode1
Federated Bayesian Optimization via Thompson SamplingCode1
An adaptive augmented Lagrangian method for training physics and equality constrained artificial neural networksCode1
Calibrating LLMs with Information-Theoretic Evidential Deep LearningCode1
CAVM: Conditional Autoregressive Vision Model for Contrast-Enhanced Brain Tumor MRI SynthesisCode1
Ferret: Federated Full-Parameter Tuning at Scale for Large Language ModelsCode1
Fast TreeSHAP: Accelerating SHAP Value Computation for TreesCode1
Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation SpaceCode1
Fast and Interpretable 2D Homography Decomposition: Similarity-Kernel-Similarity and Affine-Core-Affine TransformationsCode1
CFT-RAG: An Entity Tree Based Retrieval Augmented Generation Algorithm With Cuckoo FilterCode1
Birdie: Advancing State Space Models with Reward-Driven Objectives and CurriculaCode1
Fast and Low-Cost Genomic Foundation Models via Outlier RemovalCode1
Adaptive Focus for Efficient Video RecognitionCode1
CIS-UNet: Multi-Class Segmentation of the Aorta in Computed Tomography Angiography via Context-Aware Shifted Window Self-AttentionCode1
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image ClassificationCode1
Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and RegularizationCode1
FAMO: Fast Adaptive Multitask OptimizationCode1
Faith-Shap: The Faithful Shapley Interaction IndexCode1
Fast ABC-Boost: A Unified Framework for Selecting the Base Class in Multi-Class ClassificationCode1
Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection using Eight Million Samples Labeled with Imprecise Arrhythmia AlarmsCode1
Fast and Accurate Entity Recognition with Iterated Dilated ConvolutionsCode1
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional NetworksCode1
featsel: A framework for benchmarking of feature selection algorithms and cost functionsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified