World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
8371
World Ranking
7558
National Ranking
3285

Overview

Nanyun Peng is a researcher affiliated with the University of California, Los Angeles in the United States. Their research work primarily spans the field of Computer Science, with a focused emphasis on Artificial Intelligence. Within this broad domain, they have contributed substantially to subfields such as Computer Vision and Pattern Recognition, Information Systems, Molecular Biology, and Sociology and Political Science.

The scientist's main topics of work include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Speech and Dialogue Systems
  • Text Readability and Simplification
  • Artificial Intelligence in Games
  • Domain Adaptation and Few-Shot Learning

Nanyun Peng has an extensive publication record with a notable presence in several venues:

  • arXiv (Cornell University)
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Some of their recent papers include:

  • An Empirical Study of Training End-to-End Vision-and-Language Transformers (2022) - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • DEGREE: A Data-Efficient Generation-Based Event Extraction Model (2022) - Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • GATE: Graph Attention Transformer Encoder for Cross-lingual Relation and Event Extraction (2021) - Proceedings of the AAAI Conference on Artificial Intelligence
  • Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone (2022) - arXiv (Cornell University)
  • On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark (2022) - Findings of the Association for Computational Linguistics: ACL 2022

Frequent collaborators contributing to Nanyun Peng's research output include:

  • Kai-Wei Chang
  • Zi-Yi Dou
  • I-Hung Hsu
  • Kuan-Hao Huang
  • Prem Natarajan

Best Publications

  • Cross-Sentence N-ary Relation Extraction with Graph LSTMs

    Nanyun Peng;Hoifung Poon;Chris Quirk;Kristina Toutanova

  • An Empirical Study of Training End-to-End Vision-and-Language Transformers

    Unknown

  • Style Transfer in Text: Exploration and Evaluation

    Zhenxin Fu;Xiaoye Tan;Nanyun Peng;Dongyan Zhao

  • The Woman Worked as a Babysitter: On Biases in Language Generation

    Emily Sheng;Kai-Wei Chang;Premkumar Natarajan;Nanyun Peng

  • Named Entity Recognition for Chinese Social Media with Jointly Trained Embeddings

    Nanyun Peng;Mark Dredze

  • Plan-And-Write: Towards Better Automatic Storytelling

    Lili Yao;Nanyun Peng;Ralph M. Weischedel;Kevin Knight

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

    Nanyun Peng;Mark Dredze

  • Generalized Decoding for Pixel, Image, and Language

    Unknown

  • DEGREE: A Data-Efficient Generation-Based Event Extraction Model

    Unknown

  • Stack-Pointer Networks for Dependency Parsing.

    Xuezhe Ma;Zecong Hu;Jingzhou Liu;Nanyun Peng

  • On Difficulties of Cross-Lingual Transfer with Order Differences: A Case Study on Dependency Parsing

    Wasi Uddin Ahmad;Zhisong Zhang;Xuezhe Ma;Eduard H. Hovy

  • Multi-task Domain Adaptation for Sequence Tagging

    Nanyun Peng;Mark Dredze

  • Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone

    Unknown

  • Towards Controllable Story Generation

    Nanyun Peng;Marjan Ghazvininejad;Jonathan May;Kevin Knight

  • Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction

    Rujun Han;Qiang Ning;Nanyun Peng

  • Societal Biases in Language Generation: Progress and Challenges

    Emily Sheng;Kai-Wei Chang;Prem Natarajan;Nanyun Peng

  • Content Planning for Neural Story Generation with Aristotelian Rescoring

    Seraphina Goldfarb-Tarrant;Tuhin Chakrabarty;Ralph M. Weischedel;Nanyun Peng

  • Towards Controllable Biases in Language Generation

    Emily Sheng;Kai-Wei Chang;Premkumar Natarajan;Nanyun Peng

  • Better Automatic Evaluation of Open-Domain Dialogue Systems with Contextualized Embeddings

    Sarik Ghazarian;Johnny Tian-Zheng Wei;Aram Galstyan;Nanyun Peng

  • TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions

    Qiang Ning;Hao Wu;Rujun Han;Nanyun Peng

  • Modeling Word Forms Using Latent Underlying Morphs and Phonology

    Ryan Cotterell;Nanyun Peng;Jason Eisner

  • STORIUM: A Dataset and Evaluation Platform for Machine-in-the-Loop Story Generation

    Nader Akoury;Shufan Wang;Josh Whiting;Stephen Hood

  • Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering.

    Peifeng Wang;Nanyun Peng;Filip Ilievski;Pedro A. Szekely

  • Espresso: A Fast End-to-End Neural Speech Recognition Toolkit

    Yiming Wang;Sanjeev Khudanpur;Tongfei Chen;Hainan Xu

  • Cross-Sentence N-ary Relation Extraction with Graph LSTMs

    Nanyun Peng;Hoifung Poon;Chris Quirk;Kristina Toutanova

Frequent Co-Authors

Kai-Wei Chang
Kai-Wei Chang University of California, Los Angeles
Aram Galstyan
Aram Galstyan University of Southern California
Ralph Weischedel
Ralph Weischedel University of Southern California
Mark Dredze
Mark Dredze Johns Hopkins University
Dongyan Zhao
Dongyan Zhao Peking University
Rui Yan
Rui Yan Renmin University of China
Prem Natarajan
Prem Natarajan Capital One (United States)
Eduard Hovy
Eduard Hovy Carnegie Mellon University
Emilio Ferrara
Emilio Ferrara University of Southern California
Ryan Cotterell
Ryan Cotterell ETH Zurich

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