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 431–440 of 4891 papers

TitleStatusHype
Spectral-Spatial Mamba for Hyperspectral Image ClassificationCode1
Collaborative Filtering Based on Diffusion Models: Unveiling the Potential of High-Order ConnectivityCode1
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image ClassificationCode1
Adapting LLaMA Decoder to Vision TransformerCode1
Complex Neural Network based Joint AoA and AoD Estimation for Bistatic ISACCode1
Learning Enriched Features via Selective State Spaces Model for Efficient Image DeblurringCode1
ModeTv2: GPU-accelerated Motion Decomposition Transformer for Pairwise Optimization in Medical Image RegistrationCode1
Enhancing Vision-Language Few-Shot Adaptation with Negative LearningCode1
T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token MemoryCode1
SwinMTL: A Shared Architecture for Simultaneous Depth Estimation and Semantic Segmentation from Monocular Camera ImagesCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified