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Found 5 papers, 3 papers with code
QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference
We introduce QUICK, a group of novel optimized CUDA kernels for the efficient inference of quantized Large Language Models (LLMs).
Squeezing Large-Scale Diffusion Models for Mobile
The emergence of diffusion models has greatly broadened the scope of high-fidelity image synthesis, resulting in notable advancements in both practical implementation and academic research.
Active Learning for Deep Object Detection via Probabilistic Modeling
Most of these methods are based on multiple models or are straightforward extensions of classification methods, hence estimate an image's informativeness using only the classification head.
Deep Active Learning for Object Detection with Mixture Density Networks
For active learning, we propose a scoring function that aggregates uncertainties from both the classification and the localization outputs of the network.
Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving
Therefore, a detection algorithm that can cope with mislocalizations is required in autonomous driving applications.
