Nanyun Peng | Semantic Scholar

Publications
Influence

Style Transfer in Text: Exploration and Evaluation

Zhenxin Fu, Xiaoye Tan, Nanyun Peng, Dongyan Zhao, Rui Yan
AAAI
2017

Style transfer is an important problem in natural language processing (NLP). However, the progress in language style transfer is lagged behind other domains, such as computer vision, mainly because… (More)

Cross-Sentence N-ary Relation Extraction with Graph LSTMs

Nanyun Peng, Hoifung Poon, Chris Quirk, Kristina Toutanova, Wen-tau Yih
Transactions of the Association for Computational…
2017

Past work in relation extraction has focused on binary relations in single sentences. Recent NLP inroads in high-value domains have sparked interest in the more general setting of extracting n-ary… (More)

Named Entity Recognition for Chinese Social Media with Jointly Trained Embeddings

We consider the task of named entity recognition for Chinese social media. The long line of work in Chinese NER has focused on formal domains, and NER for social media has been largely restricted to… (More)

Stack-Pointer Networks for Dependency Parsing

Xuezhe Ma, Zecong Hu, Jingzhou Liu, Nanyun Peng, Graham Neubig, Eduard H. Hovy
ACL
2018

We introduce a novel architecture for dependency parsing: \emph{stack-pointer networks} (\textbf{\textsc{StackPtr}}). Combining pointer networks~\citep{vinyals2015pointer} with an internal stack, the… (More)

Improving Named Entity Recognition for Chinese Social Media with Word Segmentation Representation Learning

Named entity recognition, and other information extraction tasks, frequently use linguistic features such as part of speech tags or chunkings. For languages where word boundaries are not readily… (More)

Multi-task Multi-domain Representation Learning for Sequence Tagging

Representation learning with deep models have demonstrated success in a range of NLP. In this paper we consider its use in a multi-task multi-domain setting for sequence tagging by proposing a… (More)

Multi-task Domain Adaptation for Sequence Tagging

Nanyun Peng, Mark Dredze
Rep4NLP@ACL
2016

Many domain adaptation approaches rely on learning cross domain shared representations to transfer the knowledge learned in one domain to other domains. Traditional domain adaptation only considers… (More)

Stochastic Contextual Edit Distance and Probabilistic FSTs

Ryan Cotterell, Nanyun Peng, Jason Eisner
ACL
2014

String similarity is most often measured by weighted or unweighted edit distance d(x, y). Ristad and Yianilos (1998) defined stochastic edit distance—a probability distribution p(y | x) whose… (More)

Near or Far, Wide Range Zero-Shot Cross-Lingual Dependency Parsing

Wasi Uddin Ahmad, Zhisong Zhang, Xuezhe Ma, Eduard H. Hovy, Kai-Wei Chang, Nanyun Peng
ArXiv
2018

Cross-lingual transfer is the major means toleverage knowledge from high-resource lan-guages to help low-resource languages. In this paper, we investigate cross-lingual trans-fer across a broad… (More)

Plan-And-Write: Towards Better Automatic Storytelling

Lili Yao, Nanyun Peng, Ralph M. Weischedel, Kevin Knight, Dongyan Zhao, Rui Yan
AAAI
2018

Automatic storytelling is challenging since it requires generating long, coherent natural language to describes a sensible sequence of events. Despite considerable efforts on automatic story… (More)