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 2511–2520 of 4891 papers

TitleStatusHype
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level OptimizationCode0
Multilingual De-Duplication Strategies: Applying scalable similarity search with monolingual & multilingual embedding models—0
Tree-Sliced Wasserstein Distance: A Geometric Perspective—0
MVSBoost: An Efficient Point Cloud-based 3D Reconstruction—0
CLAMP: Majorized Plug-and-Play for Coherent 3D LIDAR Imaging—0
Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy InterpolationCode0
Meta Reasoning for Large Language Models—0
Explainable Bayesian Recurrent Neural Smoother to Capture Global State Evolutionary Correlations—0
MetaGPT: Merging Large Language Models Using Model Exclusive Task Arithmetic—0
SparseDet: A Simple and Effective Framework for Fully Sparse LiDAR-based 3D Object Detection—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified