World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
8145
World Ranking
9191
National Ranking
3913

Overview

Chris Quirk is affiliated with Microsoft in the United States and has contributed to research primarily in the field of Computer Science. Their work spans various subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, and Social Psychology.

The main topics in Chris Quirk's research portfolio include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Speech Recognition and Synthesis
  • Mental Health via Writing
  • Text Readability and Simplification
  • Advanced Graph Neural Networks

Chris Quirk's frequent coauthors comprise:

  • Michel Galley
  • Jianfeng Gao
  • Zeqiu Wu
  • Chris Brockett
  • Yizhe Zhang

Publications by Chris Quirk are often found in the following venues:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Findings of the Association for Computational Linguistics: ACL 2022

Among their published papers are:

  • A Controllable Model of Grounded Response Generation, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Probing Factually Grounded Content Transfer with Factual Ablation, 2022, Findings of the Association for Computational Linguistics: ACL 2022
  • Examination and Extension of Strategies for Improving Personalized Language Modeling via Interpolation, 2020, arXiv (Cornell University)
  • A Controllable Model of Grounded Response Generation, 2020, arXiv (Cornell University)
  • Probing Factually Grounded Content Transfer with Factual Ablation, 2022, arXiv (Cornell University)

Best Publications

  • Unsupervised construction of large paraphrase corpora: exploiting massively parallel news sources

    Bill Dolan;Chris Quirk;Chris Brockett

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

    Nanyun Peng;Hoifung Poon;Chris Quirk;Kristina Toutanova

  • Dependency Treelet Translation: Syntactically Informed Phrasal SMT

    Chris Quirk;Arul Menezes;Colin Cherry

  • Machine translation system incorporating syntactic dependency treelets into a statistical framework

    Arul A. Menezes;Christopher B. Quirk;Colin A. Cherry

  • Monolingual Machine Translation for Paraphrase Generation

    Chris Quirk;Chris Brockett;William B. Dolan

  • Machine Translation

    Unknown

  • Joint Language and Translation Modeling with Recurrent Neural Networks

    Michael Auli;Michel Galley;Chris Quirk;Geoffrey Zweig

  • System for identifying paraphrases using machine translation techniques

    Christopher B. Quirk;Christopher J. Brockett;William B. Dolan

  • Distant Supervision for Relation Extraction beyond the Sentence Boundary

    Chris Quirk;Hoifung Poon

  • Extracting Parallel Sentences from Comparable Corpora using Document Level Alignment

    Jason R. Smith;Chris Quirk;Kristina Toutanova

  • System for identifying paraphrases using machine translation

    Christopher J. Brockett;William B. Dolan;Christopher B. Quirk

  • Language to Code: Learning Semantic Parsers for If-This-Then-That Recipes

    Chris Quirk;Raymond Mooney;Michel Galley

  • deltaBLEU: A Discriminative Metric for Generation Tasks with Intrinsically Diverse Targets

    Michel Galley;Chris Brockett;Alessandro Sordoni;Yangfeng Ji

  • System and method for machine learning a confidence metric for machine translation

    Christopher B. Quirk;Arul A. Menezes;Stephen D. Richardson;Robert C. Moore

  • Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Text

    Kristina Toutanova;Victoria Lin;Wen-tau Yih;Hoifung Poon

  • Training a Sentence-Level Machine Translation Confidence Measure.

    Christopher B. Quirk

  • A Large Scale Ranker-Based System for Search Query Spelling Correction

    Jianfeng Gao;Xiaolong Li;Daniel Micol;Chris Quirk

  • Statistical language model for logical forms

    Anthony Aue;Eric Ringger;Christopher Quirk;Arul Menezes

  • Extracting treelet translation pairs

    Arul A. Menezes;Christopher B. Quirk;Colin A. Cherry

  • Statistical language model for logical form using transfer mappings

    Anthony Aue;Eric K. Ringger;Christopher B. Quirk;Arul A. Menezes

  • Novel positional encodings to enable tree-based transformers

    Vighnesh Leonardo Shiv;Chris Quirk

  • Book review: linguistic structure prediction noah a. smith carnegie mellon university morgan & claypool (synthesis lectures on human language technologies, edited by graeme hirst, volume 13), 2011, xx+248 pp; paperbound, isbn 978-1-60845-405-1, $60.00; ebook, isbn 978-1-60845-406-8, $30.00 or by subscription

    Chris Quirk

Frequent Co-Authors

Robert C. Moore
Robert C. Moore Google (United States)
Kristina Toutanova
Kristina Toutanova Google (United States)
Jianfeng Gao
Jianfeng Gao Microsoft (United States)
Michel Galley
Michel Galley Microsoft (United States)
Colin Cherry
Colin Cherry Google (Canada)
Chris Brockett
Chris Brockett Microsoft (United States)
Hoifung Poon
Hoifung Poon Microsoft (United States)
Wen-tau Yih
Wen-tau Yih Facebook (United States)
William B. Dolan
William B. Dolan Microsoft (United States)
Margaret Mitchell
Margaret Mitchell Hugging Face

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