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 341–350 of 4891 papers

TitleStatusHype
Automated Lane Merging via Game Theory and Branch Model Predictive ControlCode1
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time SeriesCode1
Efficient Aggregated Kernel Tests using Incomplete U-statisticsCode1
Efficient and Effective Augmentation Strategy for Adversarial TrainingCode1
Efficient Multi-scale Network with Learnable Discrete Wavelet Transform for Blind Motion DeblurringCode1
AMR Similarity Metrics from PrinciplesCode1
Dynamic-VLM: Simple Dynamic Visual Token Compression for VideoLLMCode1
Dynamic Multimodal FusionCode1
EdgeRegNet: Edge Feature-based Multimodal Registration Network between Images and LiDAR Point CloudsCode1
Dynamic Group Convolution for Accelerating Convolutional Neural NetworksCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified