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 2281–2290 of 4891 papers

TitleStatusHype
Computation and Communication Efficient Lightweighting Vertical Federated Learning for Smart Building IoT—0
SelfReplay: Adapting Self-Supervised Sensory Models via Adaptive Meta-Task Replay—0
P-Hologen: An End-to-End Generative Framework for Phase-Only HologramsCode0
Learning Enriched Features via Selective State Spaces Model for Efficient Image DeblurringCode1
Multi-scale Unified Network for Image Classification—0
Reachability Analysis Using Constrained Polynomial Logical ZonotopesCode0
Transformers-based architectures for stroke segmentation: A review—0
CCDSReFormer: Traffic Flow Prediction with a Criss-Crossed Dual-Stream Enhanced Rectified Transformer Model—0
Tiny Models are the Computational Saver for Large ModelsCode0
Retentive Decision Transformer with Adaptive Masking for Reinforcement Learning based Recommendation Systems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified