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 2041–2050 of 4891 papers

TitleStatusHype
DIPPER: Direct Preference Optimization to Accelerate Primitive-Enabled Hierarchical Reinforcement Learning—0
SparseDet: A Simple and Effective Framework for Fully Sparse LiDAR-based 3D Object Detection—0
Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object DetectionCode2
Event-Based Simulation of Stochastic Memristive Devices for Neuromorphic Computing—0
Group and Shuffle: Efficient Structured Orthogonal ParametrizationCode0
SatDiffMoE: A Mixture of Estimation Method for Satellite Image Super-resolution with Latent Diffusion Models—0
Research on Edge Detection of LiDAR Images Based on Artificial Intelligence Technology—0
DiffusionBlend: Learning 3D Image Prior through Position-aware Diffusion Score Blending for 3D Computed Tomography Reconstruction—0
Q-S5: Towards Quantized State Space ModelsCode0
FacEnhance: Facial Expression Enhancing with Recurrent DDPMs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified