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

David Chiang, Peter Cholak, and Anand Pillay. Tighter bounds on the expressivity of transformer encoders. arXiv:2301.10743. PDF BibTeX
Brian DuSell and David Chiang. The surprising computational power of nondeterministic stack RNNs. In Proc. ICLR. 2023. To appear. PDF BibTeX
David Chiang, Colin McDonald, and Chung-chieh Shan. Exact recursive probabilistic programming. PACMPL (OOPSLA), 2023. To appear. PDF BibTeX
Chihiro Taguchi and David Chiang. Introducing morphology in Universal Dependencies Japanese. In Proc. Workshop on Universal Dependencies. 2023. To appear. BibTeX
David Chiang, Alexander M. Rush, and Boaz Barak. Named tensor notation. Transactions on Machine Learning Research, 2023. PDF BibTeX
Darcey Riley and David Chiang. A continuum of generation tasks for investigating length bias and degenerate repetition. In Proc. BlackboxNLP. 2022. PDF BibTeX
Alexandra Butoi, Brian DuSell, Tim Vieira, Ryan Cotterell, and David Chiang. Algorithms for weighted pushdown automata. In Proc. EMNLP. 2022. PDF BibTeX
David Chiang and Peter Cholak. Overcoming a theoretical limitation of self-attention. In Proc. ACL. 2022. PDF BibTeX
Brian DuSell and David Chiang. Learning hierarchical structures with differentiable nondeterministic stacks. In Proc. ICLR. 2022. PDF BibTeX
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
David Chiang and Darcey Riley. Factor graph grammars. In Proc. NeurIPS, 6648–6658. 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 and David Chiang. Correcting length bias in neural machine translation. In Proc. WMT, 212–223. 2018. 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