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 441–450 of 4891 papers

TitleStatusHype
DeformUX-Net: Exploring a 3D Foundation Backbone for Medical Image Segmentation with Depthwise Deformable ConvolutionCode1
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model TrainingCode1
FastMap: Fast Queries Initialization Based Vectorized HD Map Reconstruction FrameworkCode1
Fast Point TransformerCode1
α-DPO: Adaptive Reward Margin is What Direct Preference Optimization NeedsCode1
Learning Fine-Grained Features for Pixel-wise Video CorrespondencesCode1
Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent CodingCode1
Change State Space Models for Remote Sensing Change DetectionCode1
LENSLLM: Unveiling Fine-Tuning Dynamics for LLM SelectionCode1
FastKV: KV Cache Compression for Fast Long-Context Processing with Token-Selective PropagationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified