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 881–890 of 4891 papers

TitleStatusHype
Without Paired Labeled Data: An End-to-End Self-Supervised Paradigm for UAV-View Geo-LocalizationCode2
IMTS-Mixer: Mixer-Networks for Irregular Multivariate Time Series Forecasting—0
Practical Topics in Optimization—0
Collaborative Deterministic-Probabilistic Forecasting for Real-World Spatiotemporal Systems—0
Don't Get Lost in the Trees: Streamlining LLM Reasoning by Overcoming Tree Search Exploration PitfallsCode0
Emergent functions of noise-driven spontaneous activity: Homeostatic maintenance of criticality and memory consolidation—0
CalibQuant: 1-Bit KV Cache Quantization for Multimodal LLMsCode1
RemInD: Remembering Anatomical Variations for Interpretable Domain Adaptive Medical Image Segmentation—0
Reduced Order Modeling with Shallow Recurrent Decoder NetworksCode1
Probabilistic Lexical Manifold Construction in Large Language Models via Hierarchical Vector Field Interpolation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified