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Found 6 papers, 3 papers with code
Data Mixing Made Efficient: A Bivariate Scaling Law for Language Model Pretraining
Large language models exhibit exceptional generalization capabilities, primarily attributed to the utilization of diversely sourced data.
Data-Juicer: A One-Stop Data Processing System for Large Language Models
A data recipe is a mixture of data from different sources for training LLMs, which plays a vital role in LLMs' performance.
Entropy-Driven Mixed-Precision Quantization for Deep Network Design
Deploying deep convolutional neural networks on Internet-of-Things (IoT) devices is challenging due to the limited computational resources, such as limited SRAM memory and Flash storage.
Towards automatic visual inspection: A weakly supervised learning method for industrial applicable object detection
With the recent progress of deep learning, advanced industrial object detectors are built for smart industrial applications.
Ranked #22 on
Weakly Supervised Object Detection
on PASCAL VOC 2007
OICSR: Out-In-Channel Sparsity Regularization for Compact Deep Neural Networks
Many channel pruning works utilize structured sparsity regularization to zero out all the weights in some channels and automatically obtain structure-sparse network in training stage.
Fewer is More: Image Segmentation Based Weakly Supervised Object Detection with Partial Aggregation
As most weakly supervised object detection methods are based on pre-generated proposals, they often show two false detections: (i) group multiple object instances with one bounding box, and (ii) focus on only parts rather than the whole objects.
Ranked #25 on
Weakly Supervised Object Detection
on PASCAL VOC 2007
