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

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Showing 3051–3060 of 4891 papers

TitleStatusHype
QArchSearch: A Scalable Quantum Architecture Search Package—0
Focus on Local Regions for Query-based Object Detection—0
Realizing Stabilized Landing for Computation-Limited Reusable Rockets: A Quantum Reinforcement Learning Approach—0
An Edge-Aware Graph Autoencoder Trained on Scale-Imbalanced Data for Traveling Salesman Problems—0
A Comparison between Markov Chain and Koopman Operator Based Data-Driven Modeling of Dynamical Systems—0
Task Aware Modulation using Representation Learning: An Approach for Few Shot Learning in Environmental Systems—0
QE-BEV: Query Evolution for Bird's Eye View Object Detection in Varied ContextsCode0
Can pruning make Large Language Models more efficient?—0
Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly—0
Learning to Reach Goals via DiffusionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified