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 2411–2420 of 4891 papers

TitleStatusHype
Beyond Standard MoE: Mixture of Latent Experts for Resource-Efficient Language Models—0
Efficient and Accurate Estimation of Lipschitz Constants for Hybrid Quantum-Classical Decision Models—0
Beyond Sequence: Impact of Geometric Context for RNA Property Prediction—0
Beyond Sentence-Level End-to-End Speech Translation: Context Helps—0
Beyond Reproducibility: Advancing Zero-shot LLM Reranking Efficiency with Setwise Insertion—0
Identifying and Analyzing Task-Encoding Tokens in Large Language Models—0
On the Computational Efficiency of Adaptive and Dynamic Regret Minimization—0
Efficient Active Learning for Gaussian Process Classification by Error Reduction—0
Efficient Action Recognition Using Confidence Distillation—0
Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified