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 281–290 of 4891 papers

TitleStatusHype
Neural-Inspired Advances in Integral Cryptanalysis—0
IISE PG&E Energy Analytics Challenge 2025: Hourly-Binned Regression Models Beat Transformers in Load Forecasting—0
Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach—0
LGBQPC: Local Granular-Ball Quality Peaks Clustering—0
Effective Probabilistic Time Series Forecasting with Fourier Adaptive Noise-Separated Diffusion—0
Fourier Low-rank and Sparse Tensor for Efficient Tensor Completion—0
HSRMamba: Efficient Wavelet Stripe State Space Model for Hyperspectral Image Super-ResolutionCode0
From Embeddings to Accuracy: Comparing Foundation Models for Radiographic Classification—0
Learning to Think: Information-Theoretic Reinforcement Fine-Tuning for LLMs—0
Multi-Robot Task Allocation for Homogeneous Tasks with Collision Avoidance via Spatial Clustering—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified