most citedFormality Style Transfer with Hybrid Textual Annotations

31 citations · 45 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL20201 cited

Predicting Performance for Natural Language Processing Tasks

Mengzhou Xia, Antonios Anastasopoulos, Ruochen Xu +2

Given the complexity of combinations of tasks, languages, and domains in natural language processing (NLP) research, it is computationally prohibitive to exhaustively test newly pr…

cs.CL2020

A Hierarchical Network for Abstractive Meeting Summarization with Cross-Domain Pretraining

Chenguang Zhu, Ruochen Xu, Michael Zeng +1

With the abundance of automatic meeting transcripts, meeting summarization is of great interest to both participants and other parties. Traditional methods of summarizing meetings…

cs.CL20199 cited

Cross-lingual Alignment vs Joint Training: A Comparative Study and A Simple Unified Framework

Zirui Wang, Jiateng Xie, Ruochen Xu +3

Learning multilingual representations of text has proven a successful method for many cross-lingual transfer learning tasks. There are two main paradigms for learning such represen…

cs.CL201931 cited

Formality Style Transfer with Hybrid Textual Annotations

Ruochen Xu, Tao Ge, Furu Wei

Formality style transformation is the task of modifying the formality of a given sentence without changing its content. Its challenge is the lack of large-scale sentence-aligned pa…

cs.CL20194 cited

The ARIEL-CMU Systems for LoReHLT18

Aditi Chaudhary, Siddharth Dalmia, Junjie Hu +27

This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery a…