David Chiang 蔣偉
Associate Professor, Computer Science and Engineering
Natural Language Processing Group
My research is in natural language processing, the subfield of computer science that aims to enable computers to understand and produce human language. I focus mainly on language translation, and am interested in syntactic parsing and other areas as well.
Teaching
- Spring 2021: CSE 40657/60657, Natural Language Processing
- Fall 2020: CSE 30151, Theory of Computing
- Spring 2020: CSE 30151, Theory of Computing
- Fall 2019: CSE 40657/60657, Natural Language Processing
- Spring 2019: CSE 40431, Programming Languages
Recent and selected publications
Xing Jie Zhong and David Chiang.
Look it up: bilingual and monolingual dictionaries improve neural machine translation.
In Proc. WMT. 2020.
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Brian DuSell and David Chiang.
Learning context-free languages with nondeterministic stack RNNs.
In Proc. CoNLL, 507–519. 2020.
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Justin DeBenedetto and David Chiang.
Representing unordered data using complex-weighted multiset automata.
In Hal Daumé III and Aarti Singh, editors, Proc. ICML, volume 119 of Proceedings of Machine Learning Research, 2412–2420. 2020.
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Kenton Murray, Jeffery Kinnison, Toan Q. Nguyen, Walter Scheirer, and David Chiang.
Auto-sizing the Transformer network: improving speed, efficiency, and performance for low-resource machine translation.
In Proc. Workshop on Neural Generation and Translation, 231–240. 2019.
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Arturo Argueta and David Chiang.
Accelerating sparse matrix operations in neural networks on graphics processing units.
In Proc. ACL, 6215–6224. 2019.
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Antonios Anastasopoulos, Alison Lui, Toan Q. Nguyen, and David Chiang.
Neural machine translation of text from non-native speakers.
In Proc. NAACL: HLT, volume 1, 3070–3080. 2019.
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Kenton Murray and David Chiang.
Correcting length bias in neural machine translation.
In Proc. WMT, 212–223. 2018.
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Arturo Argueta and David Chiang.
Composing finite state transducers on GPUs.
In Proc. ACL, 2697–2705. 2018.
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Justin DeBenedetto and David Chiang.
Algorithms and training for weighted multiset automata and regular expressions.
In Proc. Conference on Implementation and Applications of Automata, 146–158. 2018.
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Antonios Anastasopoulos and David Chiang.
Leveraging translations for speech transcription in low-resource settings.
In Proc. INTERSPEECH. 2018.
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Antonios Anastasopoulos and David Chiang.
Tied multitask learning for neural speech translation.
In Proc. NAACL: HLT, volume 1, 82–91. 2018.
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Toan Nguyen and David Chiang.
Improving lexical choice in neural machine translation.
In Proc. NAACL: HLT, volume 1, 334–343. 2018.
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Salvador Aguinaga, David Chiang, and Tim Weninger.
Learning hyperedge replacement grammars for graph generation.
IEEE Trans. Pattern Analysis and Machine Intelligence, 41(3):625–638, 2019.
doi:10.1109/TPAMI.2018.2810877.
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David Chiang, Frank Drewes, Adam Lopez, and Giorgio Satta.
Weighted DAG automata for semantic graphs.
Computational Linguistics, 44(1):119–186, 2018.
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Students
Current
Former
- Kenton Murray (PhD 2020 → postdoc JHU)
- Antonios Anastasopoulos (PhD 2019 → postdoc CMU → asst. prof GMU)
- Arturo Argueta (PhD 2019 → Apple)
- Cindy Xinyi Wang (BS, 2017 → CMU)
- Tomer Levinboim (PhD, 2017 → Google)
- Theerawat Dome Songyot (on leave)
- Hui Zhang (on leave → Facebook Research)
- Ashish Vaswani (PhD, 2014 → Google Brain)
- Victoria Fossum (postdoc → Google)