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

Showing 251260 of 4891 papers

TitleStatusHype
FilterTS: Comprehensive Frequency Filtering for Multivariate Time Series ForecastingCode1
Multi-View Learning with Context-Guided Receptance for Image DenoisingCode1
Small Clips, Big Gains: Learning Long-Range Refocused Temporal Information for Video Super-ResolutionCode1
LENSLLM: Unveiling Fine-Tuning Dynamics for LLM SelectionCode1
Fast and Low-Cost Genomic Foundation Models via Outlier RemovalCode1
Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context LearningCode1
Geometry-Informed Neural Operator TransformerCode1
TableCenterNet: A one-stage network for table structure recognitionCode1
Survey of Video Diffusion Models: Foundations, Implementations, and ApplicationsCode1
Exploring _0 Sparsification for Inference-free Sparse RetrieversCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified