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 3011–3020 of 4891 papers

TitleStatusHype
The use of deep learning in image segmentation, classification and detection—0
The Variational Bayesian Inference for Network Autoregression Models—0
The Weak Form Is Stronger Than You Think—0
THINK-Bench: Evaluating Thinking Efficiency and Chain-of-Thought Quality of Large Reasoning Models—0
Think Beyond Size: Adaptive Prompting for More Effective Reasoning—0
Threshold Neuron: A Brain-inspired Artificial Neuron for Efficient On-device Inference—0
Threshold Strategy for Leaking Corner-Free Hamilton-Jacobi Reachability with Decomposed Computations—0
Tighter sparse variational Gaussian processes—0
Tightly Coupled Learning Strategy for Weakly Supervised Hierarchical Place Recognition—0
TIM: An Efficient Temporal Interaction Module for Spiking Transformer—0
Show:102550
← PrevPage 302 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified