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 2371–2380 of 4891 papers

TitleStatusHype
Efficient Detector Adaptation for Object Detection in a Video—0
Efficient Detection of Toxic Prompts in Large Language Models—0
A High-Performance Object Proposals based on Horizontal High Frequency Signal—0
Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Training—0
Efficient Degradation-aware Any Image Restoration—0
Efficient Data Shapley for Weighted Nearest Neighbor Algorithms—0
Efficient Data-Driven Geologic Feature Detection from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm—0
An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning—0
Efficient Cross-Task Prompt Tuning for Few-Shot Conversational Emotion Recognition—0
EfficientCrackNet: A Lightweight Model for Crack Segmentation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified