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 3876–3900 of 4891 papers

TitleStatusHype
Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues—0
On the workflow, opportunities and challenges of developing foundation model in geophysics—0
On Vision Transformers for Classification Tasks in Side-Scan Sonar Imagery—0
OpenSlot: Mixed Open-Set Recognition with Object-Centric Learning—0
Open-Source Drift Detection Tools in Action: Insights from Two Use Cases—0
OpenSplat3D: Open-Vocabulary 3D Instance Segmentation using Gaussian Splatting—0
Operator Learning for Robust Stabilization of Linear Markov-Jumping Hyperbolic PDEs—0
opp/ai: Optimistic Privacy-Preserving AI on Blockchain—0
OptiGait-LGBM: An Efficient Approach of Gait-based Person Re-identification in Non-Overlapping Regions—0
Optimal Approximate Matrix Multiplication over Sliding Windows—0
Optimal Bounds for Private Minimum Spanning Trees via Input Perturbation—0
Optimal Control for Discrete-Time Systems under Bounded Disturbances—0
Optimal Coupled Sensor Placement and Path-Planning in Unknown Time-Varying Environments—0
Optimal Depth of Neural Networks—0
Optimal Design of Neural Network Structure for Power System Frequency Security Constraints—0
Optimal Distributed Subsampling for Maximum Quasi-Likelihood Estimators with Massive Data—0
Optimal Downsampling for Imbalanced Classification with Generalized Linear Models—0
Optimal Gradient Checkpointing for Sparse and Recurrent Architectures using Off-Chip Memory—0
Optimal Hardening Strategy for Electricity-Hydrogen Networks with Hydrogen Leakage Risk Control against Extreme Weather—0
Optimal Lattice Boltzmann Closures through Multi-Agent Reinforcement Learning—0
Non-iterative generation of an optimal mesh for a blade passage using deep reinforcement learning—0
Optimal Operation of Power Systems with Energy Storage under Uncertainty: A Scenario-based Method with Strategic Sampling—0
Optimal Clustering with Dependent Costs in Bayesian Networks—0
Optimal Sampling Designs for Multi-dimensional Streaming Time Series with Application to Power Grid Sensor Data—0
Optimal Scaling Laws for Efficiency Gains in a Theoretical Transformer-Augmented Sectional MoE Framework—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified