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 426–450 of 4891 papers

TitleStatusHype
ACEnet: Anatomical Context-Encoding Network for Neuroanatomy SegmentationCode1
FedPop: Federated Population-based Hyperparameter TuningCode1
Finer-CAM: Spotting the Difference Reveals Finer Details for Visual ExplanationCode1
Deep Implicit Moving Least-Squares Functions for 3D ReconstructionCode1
A deep inverse reinforcement learning approach to route choice modeling with context-dependent rewardsCode1
A machine learning-based viscoelastic-viscoplastic model for epoxy nanocomposites with moisture contentCode1
DeePoly: A High-Order Accuracy Scientific Machine Learning Framework for Function Approximation and Solving PDEsCode1
Language Model Uncertainty Quantification with Attention ChainCode1
Fast Sequence Based Embedding with Diffusion GraphsCode1
Fast Sequence-Based Embedding with Diffusion GraphsCode1
Deep reinforcement learning for large-scale epidemic controlCode1
M3-Jepa: Multimodal Alignment via Multi-directional MoE based on the JEPA frameworkCode1
Latent Diffusion Prior Enhanced Deep Unfolding for Snapshot Spectral Compressive ImagingCode1
LDM-Morph: Latent diffusion model guided deformable image registrationCode1
An MRC Framework for Semantic Role LabelingCode1
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