14 citations · 16 across the 4 of their papers we have counts for
4 papers
P2Skill: Privacy Preserving Skill Distillation for Cloud-Local LLM Inference Systems
Myunghoon Ryu, Geunpyo Park, Sungjoon Lee +2
Cloud-local LLM inference can use the reasoning capability of large cloud models, but cloud-bound requests must exclude personally identifiable information (PII). Existing privacy-…
Dataloader Parameter Tuner: An Automated Dataloader Parameter Tuner for Deep Learning Models
JooYoung Park, DoangJoo Synn, XinYu Piao +1
Deep learning has recently become one of the most compute/data-intensive methods and is widely used in many research areas and businesses. One of the critical challenges of deep le…
Enabling Large Batch Size Training for DNN Models Beyond the Memory Limit While Maintaining Performance
XinYu Piao, DoangJoo Synn, JooYoung Park +1
Recent deep learning models are difficult to train using a large batch size, because commodity machines may not have enough memory to accommodate both the model and a large data ba…
Contextual Skipgram: Training Word Representation Using Context Information
Dongjae Kim, Jong-Kook Kim
The skip-gram (SG) model learns word representation by predicting the words surrounding a center word from unstructured text data. However, not all words in the context window cont…