Research

Working Papers (Submitted for Review)

Allen Schmaltz. 2019. Detecting Local Insights from Global Labels: Supervised & Zero-Shot Sequence Labeling via a Convolutional Decomposition. arXiv preprint arXiv:1906.01154v4.

Natural Language Processing

Allen Schmaltz. 2019. Learning to Order & Learning to Correct. Harvard University, Ph.D. dissertation, Computer Science.

Allen Schmaltz, Yoon Kim, Alexander Rush, and Stuart Shieber. 2017. Adapting Sequence Models for Sentence Correction. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2807-2813, Copenhagen, Denmark, September. Association for Computational Linguistics. https://www.aclweb.org/anthology/D17-1298. (Appendix) (.bib)

Allen Schmaltz, Alexander M. Rush, and Stuart Shieber. 2016. Word Ordering Without Syntax. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 2319-2324, Austin, TX, USA, November. Association for Computational Linguistics. https://aclweb.org/anthology/D16-1255. (.bib)

Allen Schmaltz, Yoon Kim, Alexander M. Rush, and Stuart Shieber. 2016. Sentence-Level Grammatical Error Identification as Sequence-to-Sequence Correction. In Proceedings of the 11th Workshop on Innovative Use of NLP for Building Educational Applications, pages 242-251, San Diego, CA, USA, June. Association for Computational Linguistics. https://www.aclweb.org/anthology/W16-0528. (.bib)

Medicine and Public Health

Andrew L. Beam, Benjamin Kompa, Allen Schmaltz, Inbar Fried, Griffin Weber, Nathan P. Palmer, Xu Shi, Tianxi Cai, Isaac S. Kohane. 2019. Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data. arXiv preprint arXiv:1804.01486v3. To appear at the Pacific Symposium on Biocomputing (PSB) 2020.

Public Policy

Allen Schmaltz. 2018. On the Utility of Lay Summaries and AI Safety Disclosures: Toward Robust, Open Research Oversight. In Proceedings of the Second ACL Workshop on Ethics in Natural Language Processing, pages 1-6, New Orleans, LA, USA, June. Association for Computational Linguistics. https://aclweb.org/anthology/W18-0801. (.bib)

Quantitative Social Science

Wenxin Jiang, Gary King, Allen Schmaltz, and Martin A. Tanner. 2019. Ecological Regression with Partial Identification. Political Analysishttps://doi.org/10.1017/pan.2019.19.