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 2351–2360 of 4891 papers

TitleStatusHype
Enhancing Transferability of Adversarial Attacks with GE-AdvGAN+: A Comprehensive Framework for Gradient Editing—0
Deep Learning Improvements for Sparse Spatial Field Reconstruction—0
MambaOcc: Visual State Space Model for BEV-based Occupancy Prediction with Local Adaptive ReorderingCode0
Quantifying Behavioural Distance Between Mathematical Expressions—0
Efficient Detection of Toxic Prompts in Large Language Models—0
EE-MLLM: A Data-Efficient and Compute-Efficient Multimodal Large Language Model—0
Approximation of the Proximal Operator of the _ Norm Using a Neural NetworkCode0
A Lightweight Modular Framework for Low-Cost Open-Vocabulary Object Detection TrainingCode0
UKAN: Unbound Kolmogorov-Arnold Network Accompanied with Accelerated Library—0
HMoE: Heterogeneous Mixture of Experts for Language Modeling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified