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 4291–4300 of 4891 papers

TitleStatusHype
Efficient Language Model Architectures for Differentially Private Federated Learning—0
Efficient Large-Scale Multi-Modal Classification—0
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer—0
LREA: Low-Rank Efficient Attention on Modeling Long-Term User Behaviors for CTR Prediction—0
Efficiently Expanding Receptive Fields: Local Split Attention and Parallel Aggregation for Enhanced Large-scale Point Cloud Semantic Segmentation—0
Efficiently Predicting Protein Stability Changes Upon Single-point Mutation with Large Language Models—0
Efficient Malware Detection with Optimized Learning on High-Dimensional Features—0
Efficient Meta-Learning for Continual Learning with Taylor Expansion Approximation—0
Efficient Model Agnostic Approach for Implicit Neural Representation Based Arbitrary-Scale Image Super-Resolution—0
Efficient MPC for Emergency Evasive Maneuvers, Part II: Comparative Assessment for Hybrid Control—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified