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

Andy Yang, Pascal Bergsträßer, Georg Zetzsche, David Chiang, and Anthony W. Lin. Length generalization bounds for transformers. In Proc. ICML. 2026. To appear. PDF BibTeX
Chihiro Taguchi, Yukinori Takubo, and David Chiang. Automatic speech recognition for documenting endangered languages: case study of Ikema Miyakoan. In Proc. Language Resources and Evaluation Conference. 2026. To appear. PDF BibTeX
Stephen Bothwell, Kaitlin Stephan, Hildegund Müller, and David Chiang. From paginā to webpage: on developing and documenting a digitized Latin collection. Journal of Open Humanities Data, 2026. doi:10.5334/johd.397. DOI BibTeX
Akriti Dhasmana, Aarohi Srivastava, and David Chiang. Dialect matters: cross-lingual ASR transfer for low-resource Indic language varieties. In Proc. Workshop on NLP for Similar Languages, Varieties and Dialects. 2026. PDF BibTeX
Andy Yang, Anej Svete, Jiaoda Li, Anthony Widjaja Lin, Jonathan Rawski, Ryan Cotterell, and David Chiang. Probability distributions computed by autoregressive transformers. In Proc. ICLR. 2026. To appear. PDF BibTeX
Andy Yang, Christopher Watson, Anton Xue, Satwik Bhattamishra, Jose Llarena, William Merrill, Emile Dos Santos Ferreira, Anej Svete, and David Chiang. The transformer cookbook. Transactions on Machine Learning Research, January 2026. PDF BibTeX
Katsumi Ibaraki and David Chiang. Frustratingly easy data augmentation for low-resource ASR. 2025. arXiv:2509.15373. PDF BibTeX
Chihiro Taguchi, Seng Mai, Keita Kurabe, Yusuke Sakai, Georgina Agyei, Soudabeh Eslami, and David Chiang. Languages still left behind: toward a better multilingual machine translation benchmark. In Proc. EMNLP, 20142–20154. 2025. doi:10.18653/v1/2025.emnlp-main.1018. PDF BibTeX
Andy Yang, Michaël Cadilhac, and David Chiang. Knee-deep in C-RASP: a transformer depth hierarchy. In Proc. NeurIPS 38. 2025. To appear. PDF BibTeX
Andy Yang, Lena Strobl, David Chiang, and Dana Angluin. Simulating hard attention using soft attention. Transactions of the Association for Computational Linguistics, 14:147–166, 2026. doi:10.1162/TACL.a.597. DOI BibTeX
Aarohi Srivastava and David Chiang. We're calling an intervention: exploring fundamental hurdles in adapting language models to nonstandard text. In Proc. Workshop on Noisy and User-Generated Text. 2025. Best Paper Award. PDF BibTeX
David Chiang. Transformers in uniform TC\(^0\). Transactions on Machine Learning Research, January 2025. PDF BibTeX
Lena Strobl, Dana Angluin, David Chiang, Jonathan Rawski, and Ashish Sabharwal. Transformers as transducers. Transactions of the Association for Computational Linguistics, 13:200–219, 2025. doi:10.1162/tacl_a_00736. DOI BibTeX
Chihiro Taguchi and David Chiang. Language complexity and speech recognition accuracy: orthographic complexity hurts, phonological complexity doesn't. In Proc. ACL. 2024. Outstanding Paper Award and Senior Area Chair Award. PDF BibTeX
Fahim Faisal, Orevaoghene Ahia, Aarohi Srivastava, Kabir Ahuja, David Chiang, Yulia Tsvetkov, and Antonios Anastasopoulos. DIALECTBENCH: a NLP benchmark for dialects, varieties, and closely-related languages. In Proc. ACL. 2024. Social Impact Award. PDF BibTeX
David Chiang, Colin McDonald, and Chung-chieh Shan. Exact recursive probabilistic programming. PACMPL, 2023. doi:10.1145/3586050. PDF BibTeX

full list