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 2176–2200 of 4891 papers

TitleStatusHype
DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representation—0
Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Data—0
FLOPS: Forward Learning with OPtimal Sampling—0
Quantum-Inspired Portfolio Optimization In The QUBO Framework—0
Accelerating the discovery of low-energy structure configurations: a computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning—0
Bayesian Estimation and Tuning-Free Rank Detection for Probability Mass Function Tensors—0
Diffusion Models in 3D Vision: A Survey—0
SegINR: Segment-wise Implicit Neural Representation for Sequence Alignment in Neural Text-to-Speech—0
IGroupSS-Mamba: Interval Group Spatial-Spectral Mamba for Hyperspectral Image Classification—0
Granular Ball Twin Support Vector MachineCode0
CR-CTC: Consistency regularization on CTC for improved speech recognition—0
GARLIC: LLM-Guided Dynamic Progress Control with Hierarchical Weighted Graph for Long Document QA—0
SPikE-SSM: A Sparse, Precise, and Efficient Spiking State Space Model for Long Sequences Learning—0
Bisimulation metric for Model Predictive ControlCode0
Upsample or Upweight? Balanced Training on Heavily Imbalanced Datasets—0
Spectral Densities, Structured Noise and Ensemble Averaging within Open Quantum Dynamics—0
Never Mind The No-Ops: Faster and Less Volatile Simulation Modelling of Co-Evolutionary Species Interactions via Spatial Cyclic GamesCode0
Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributions—0
Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal TransportCode0
S7: Selective and Simplified State Space Layers for Sequence Modeling—0
A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical SystemsCode0
STONE: A Submodular Optimization Framework for Active 3D Object DetectionCode0
Remember and Recall: Associative-Memory-based Trajectory Prediction—0
Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement—0
Efficient Second-Order Neural Network Optimization via Adaptive Trust Region Methods—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified