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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2561–2570 of 4891 papers

TitleStatusHype
YOCO: A Hybrid In-Memory Computing Architecture with 8-bit Sub-PetaOps/W In-Situ Multiply Arithmetic for Large-Scale AI—0
A Multimodal Approach for Advanced Pest Detection and Classification—0
Linear Attention via Orthogonal Memory—0
Global-Local MAV Detection under Challenging Conditions based on Appearance and MotionCode1
Agent Assessment of Others Through the Lens of Self—0
Fast Decision Boundary based Out-of-Distribution DetectorCode0
Video-based Surgical Skill Assessment using Tree-based Gaussian Process Classifier—0
A Hierarchical Nearest Neighbour Approach to Contextual Bandits—0
FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated LearningCode1
Agent Attention: On the Integration of Softmax and Linear AttentionCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified