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 991–1000 of 4891 papers

TitleStatusHype
LoTA-QAF: Lossless Ternary Adaptation for Quantization-Aware Fine-TuningCode0
Learning Latent Variable Models via Jarzynski-adjusted Langevin Algorithm—0
CONCORD: Concept-Informed Diffusion for Dataset DistillationCode0
SEvoBench : A C++ Framework For Evolutionary Single-Objective Optimization Benchmarking—0
Improved Algorithms for Overlapping and Robust Clustering of Edge-Colored Hypergraphs: An LP-Based Combinatorial Approach—0
A tensor network approach for chaotic time series predictionCode0
Hard Negative Mining for Domain-Specific Retrieval in Enterprise Systems—0
Coverage Path Planning For Multi-view SAR-UAV Observation System Under Energy Constraint—0
Computing Exact Shapley Values in Polynomial Time for Product-Kernel Methods—0
Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified