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

Recent and selected publications

Samuel Grieggs, Bingyu Shen, Greta Rauch, Pei Li, Jiaqi Ma, David Chiang, Brian Price, and Walter Scheirer. Measuring human perception to improve handwritten document transcription. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021. doi:10.1109/TPAMI.2021.3092688. DOI BibTeX
Toan Q. Nguyen, Kenton Murray, and David Chiang. Data augmentation by concatenation for low-resource translation: a mystery and a solution. In Proc. Conference on Spoken Language Translation. 2021. To appear. PDF BibTeX
David Chiang and Colin McDonald. Syntax-based attention masking for neural machine translation. In Proc. NAACL Student Research Workshop. 2021. PDF BibTeX
David Chiang, Alexander M. Rush, and Boaz Barak. Named tensor notation. arXiv:2102.13196. PDF BibTeX
David Chiang and Chung-chieh Shan. Translating recursive probabilistic programs to factor graph grammars. 2020. Presented at PROBPROG 2020. PDF BibTeX
David Chiang and Darcey Riley. Factor graph grammars. In Proc. NeurIPS. 2020. PDF BibTeX
Brian DuSell and David Chiang. Learning context-free languages with nondeterministic stack RNNs. In Proc. CoNLL, 507–519. 2020. PDF BibTeX
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. PDF BibTeX
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. PDF BibTeX
Arturo Argueta and David Chiang. Accelerating sparse matrix operations in neural networks on graphics processing units. In Proc. ACL, 6215–6224. 2019. PDF BibTeX
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. PDF BibTeX
Kenton Murray and David Chiang. Correcting length bias in neural machine translation. In Proc. WMT, 212–223. 2018. PDF BibTeX
Arturo Argueta and David Chiang. Composing finite state transducers on GPUs. In Proc. ACL, 2697–2705. 2018. PDF BibTeX
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. PDF BibTeX
Antonios Anastasopoulos and David Chiang. Leveraging translations for speech transcription in low-resource settings. In Proc. INTERSPEECH. 2018. PDF BibTeX
Antonios Anastasopoulos and David Chiang. Tied multitask learning for neural speech translation. In Proc. NAACL: HLT, volume 1, 82–91. 2018. PDF BibTeX
Toan Nguyen and David Chiang. Improving lexical choice in neural machine translation. In Proc. NAACL: HLT, volume 1, 334–343. 2018. PDF BibTeX
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. PDF BibTeX
David Chiang, Frank Drewes, Daniel Gildea, Adam Lopez, and Giorgio Satta. Weighted DAG automata for semantic graphs. Computational Linguistics, 44(1):119–186, 2018. PDF BibTeX

full list