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 1581–1590 of 4891 papers

TitleStatusHype
Efficient Robust Conformal Prediction via Lipschitz-Bounded NetworksCode0
Boundary Graph Neural Networks for 3D SimulationsCode0
CRISP: Hybrid Structured Sparsity for Class-aware Model PruningCode0
Falcon: Fair Active Learning using Multi-armed BanditsCode0
FAMED-Net: A Fast and Accurate Multi-scale End-to-end Dehazing NetworkCode0
Faithful Group Shapley ValueCode0
Exploring Tokenization Strategies and Vocabulary Sizes for Enhanced Arabic Language ModelsCode0
Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving RegularizationCode0
FairViT: Fair Vision Transformer via Adaptive MaskingCode0
Exploring Molecule Generation Using Latent Space Graph DiffusionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified