1 code implementation • NAACL (NUSE) 2021 • Michael Yoder, Sopan Khosla, Qinlan Shen, Aakanksha Naik, Huiming Jin, Hariharan Muralidharan, Carolyn Rosé
The pipeline includes modules for character identification and coreference, as well as the attribution of quotes and narration to those characters.
1 code implementation • EACL (AdaptNLP) 2021 • Mandy Guo, Yinfei Yang, Daniel Cer, Qinlan Shen, Noah Constant
Retrieval question answering (ReQA) is the task of retrieving a sentence-level answer to a question from an open corpus (Ahmad et al., 2019). This dataset paper presents MultiReQA, a new multi-domain ReQA evaluation suite composed of eight retrieval QA tasks drawn from publicly available QA datasets.
no code implementations • EACL 2021 • Qinlan Shen, Carolyn Rose
In this paper, we challenge the assumption that political ideology is inherently built into text by presenting an investigation into the impact of experiential factors on annotator perceptions of political ideology.
1 code implementation • 5 May 2020 • Mandy Guo, Yinfei Yang, Daniel Cer, Qinlan Shen, Noah Constant
Retrieval question answering (ReQA) is the task of retrieving a sentence-level answer to a question from an open corpus (Ahmad et al., 2019). This paper presents MultiReQA, anew multi-domain ReQA evaluation suite com-posed of eight retrieval QA tasks drawn from publicly available QA datasets.
1 code implementation • 3 Apr 2020 • Samuel Läubli, Sheila Castilho, Graham Neubig, Rico Sennrich, Qinlan Shen, Antonio Toral
The quality of machine translation has increased remarkably over the past years, to the degree that it was found to be indistinguishable from professional human translation in a number of empirical investigations.
1 code implementation • WS 2019 • Qinlan Shen, Carolyn Rose
Recent concerns over abusive behavior on their platforms have pressured social media companies to strengthen their content moderation policies.
no code implementations • 22 Feb 2019 • Yinfei Yang, Gustavo Hernandez Abrego, Steve Yuan, Mandy Guo, Qinlan Shen, Daniel Cer, Yun-Hsuan Sung, Brian Strope, Ray Kurzweil
On the UN document-level retrieval task, document embeddings achieve around 97% on P@1 for all experimented language pairs.
no code implementations • WS 2018 • Mandy Guo, Qinlan Shen, Yinfei Yang, Heming Ge, Daniel Cer, Gustavo Hernandez Abrego, Keith Stevens, Noah Constant, Yun-Hsuan Sung, Brian Strope, Ray Kurzweil
This paper presents an effective approach for parallel corpus mining using bilingual sentence embeddings.
1 code implementation • NAACL 2018 • Yohan Jo, Shivani Poddar, Byungsoo Jeon, Qinlan Shen, Carolyn P. Rose, Graham Neubig
We present a neural architecture for modeling argumentative dialogue that explicitly models the interplay between an Opinion Holder's (OH's) reasoning and a challenger's argument, with the goal of predicting if the argument successfully changes the OH's view.
no code implementations • COLING 2016 • Qinlan Shen, Daniel Clothiaux, Emily Tagtow, Patrick Littell, Chris Dyer
While morphological analyzers can reduce this sparsity by providing morpheme-level analyses for words, they will often introduce ambiguity by returning multiple analyses for the same surface form.