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 2521–2530 of 4891 papers

TitleStatusHype
DIPPER: Direct Preference Optimization to Accelerate Primitive-Enabled Hierarchical Reinforcement Learning—0
Group and Shuffle: Efficient Structured Orthogonal ParametrizationCode0
DiffusionBlend: Learning 3D Image Prior through Position-aware Diffusion Score Blending for 3D Computed Tomography Reconstruction—0
Event-Based Simulation of Stochastic Memristive Devices for Neuromorphic Computing—0
Research on Edge Detection of LiDAR Images Based on Artificial Intelligence Technology—0
SatDiffMoE: A Mixture of Estimation Method for Satellite Image Super-resolution with Latent Diffusion Models—0
Q-S5: Towards Quantized State Space ModelsCode0
FacEnhance: Facial Expression Enhancing with Recurrent DDPMs—0
YOLO11 to Its Genesis: A Decadal and Comprehensive Review of The You Only Look Once (YOLO) Series—0
RILe: Reinforced Imitation Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified