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Yuntian DengPh.D. StudentHarvard University [CV] [Google Scholar] [Email] |
My research aims at enabling ubiquitous long-form text generation, where anyone can produce a document on any topic with just a few clicks. To achieve this goal, my research focuses on the following three directions, utilizing advances in deep learning combined with probabilistic modeling:
- Long-Form Coherence to generate coherent documents with self-consistency and clear transitions.
- Transparent Generation to enable users to understand, debug, and control document generation.
- Efficient Systems to handle the scale and real-time requirements of long-form text generation.
I also work on open-source projects such as OpenNMT, Im2LaTeX, LaTeX2Im, and Steganography to make my research efforts more readily available for developers and researchers.
Statements
[Research Statement] [Teaching Statement] [Interdisciplinary Statement] [Diversity Statement]Selected Papers
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Markup-to-Image Diffusion Models with Scheduled Sampling
Yuntian Deng, Noriyuki Kojima, Alexander M. Rush. ICLR 2023 |
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Model Criticism for Long-Form Text Generation
Yuntian Deng, Volodymyr Kuleshov, Alexander M Rush. EMNLP 2022 |
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Cascaded Text Generation with Markov Transformers
Yuntian Deng, Alexander M. Rush. NeurIPS 2020 |
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Residual Energy-Based Models for Text Generation
Yuntian Deng, Anton Bakhtin, Myle Ott, Arthur Szlam, Marc'Aurelio Ranzato. ICLR 2020 |
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Latent Alignment and Variational Attention
Yuntian Deng*, Yoon Kim*, Justin Chiu, Demi Guo, Alexander M. Rush. NIPS 2018 |
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Image-to-Markup Generation with Coarse-to-Fine Attention
Yuntian Deng, Anssi Kanervisto, Jeffrey Ling, and Alexander M. Rush. ICML 2017 |
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Neural Linguistic Steganography
Zachary Ziegler*, Yuntian Deng*, Alexander Rush. EMNLP 2019 (Oral) |
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OpenNMT: Open-Source Toolkit for Neural Machine Translation
Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, Alexander M. Rush. ACL Demo 2017 (Best Demo Runner-up) |
Contact
Science and Engineering Complex 5.443
150 Western Avenue
Boston, MA 02134
USA
150 Western Avenue
Boston, MA 02134
USA