19 citations · 35 across the 4 of their papers we have counts for
4 papers
Learning to Summarize Long Texts with Memory Compression and Transfer
Jaehong Park, Jonathan Pilault, Christopher Pal
We introduce Mem2Mem, a memory-to-memory mechanism for hierarchical recurrent neural network based encoder decoder architectures and we explore its use for abstractive document sum…
On the impressive performance of randomly weighted encoders in summarization tasks
Jonathan Pilault, Jaehong Park, Christopher Pal
In this work, we investigate the performance of untrained randomly initialized encoders in a general class of sequence to sequence models and compare their performance with that of…
Building a Neural Machine Translation System Using Only Synthetic Parallel Data
Jaehong Park, Jongyoon Song, Sungroh Yoon
Recent works have shown that synthetic parallel data automatically generated by translation models can be effective for various neural machine translation (NMT) issues. In this stu…
DeepSpark: A Spark-Based Distributed Deep Learning Framework for Commodity Clusters
Hanjoo Kim, Jaehong Park, Jaehee Jang +1
The increasing complexity of deep neural networks (DNNs) has made it challenging to exploit existing large-scale data processing pipelines for handling massive data and parameters…