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 751–760 of 4891 papers

TitleStatusHype
How Well Can Differential Privacy Be Audited in One Run?—0
Discrete Gaussian Process Representations for Optimising UAV-based Precision Weed Mapping—0
Small Vision-Language Models: A Survey on Compact Architectures and Techniques—0
Steerable Pyramid Weighted Loss: Multi-Scale Adaptive Weighting for Semantic Segmentation—0
VORTEX: Challenging CNNs at Texture Recognition by using Vision Transformers with Orderless and Randomized Token EncodingsCode0
M^3amba: CLIP-driven Mamba Model for Multi-modal Remote Sensing ClassificationCode1
InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models—0
Joint Location and Velocity Estimation and Fundamental CRLB Analysis for Cell-Free MIMO-ISAC—0
Emulating Self-attention with Convolution for Efficient Image Super-ResolutionCode2
Seesaw: High-throughput LLM Inference via Model Re-sharding—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified