Alexander Rush Associate Professor. Cornell University CS+Cornell Tech (NYC), Cornell NLP [arush@cornell.edu] [cv] Researcher. Hugging Face

My research aims to build NLP systems that are safe, fast, and controllable. We are interested primarily in tasks that involve text generation such as machine translation, document summarization, and data-to-text generation. Methodologically, we study data-driven probabilistic methods that combine deep-learning based models with probabilistic controls.

I am also interested in open-source NLP and deep learning, and develop projects to make deep learning systems safer, more clear, and easier to use. I work part-time at Hugging Face and like to release various software projects to support NLP and DL research.

Current Research Areas

• Interpretable and controllable natural language generation for data-to-text summary.
• Deep generative models for probabilistic text processing and understanding.
• Efficient algorithms and hardware for speech, translation, and dialogue.
• Visual tools for understanding of neural language models.

Recognition

My group's work has been recognized with an NSF CAREER Award and a Sloan Fellowship. We have won paper awards at conferences for NLP, Hardware, and Visualization, as well as awards for best demonstrations for open-source software.

Selected Papers

A selection of papers from the last five years that represent my research interests and style.

	Multitask prompted training enables zero-shot task generalization Victor Sanh, et al.. ICLR 2022
	How many data points is a prompt worth? Teven Le Scao, Alexander M. Rush. NAACL Short 2021
	Transformers: State-of-the-art Natural Language Processing Thomas Wolf et al. EMNLP Demos 2020
	Compound Probabilistic Context-Free Grammars for Grammar Induction Yoon Kim, Chris Dyer, Alexander M. Rush. ACL 2019
	Learning Neural Templates for Text Generation Sam Wiseman, Stuart M. Shieber, Alexander Rush. EMNLP 2018
	LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks Hendrik Strobelt, Sebastian Gehrmann, Hanspeter Pfister, and Alexander M. Rush. InfoVis 2017
	OpenNMT: Open-Source Toolkit for Neural Machine Translation Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, Alexander M. Rush. ACL Demo 2017
	Sequence-Level Knowledge Distillation Yoon Kim and Alexander M. Rush. EMNLP 2016
	Character-Aware Neural Language Models Yoon Kim, Yacine Jernite, David Sontag, and Alexander M. Rush. AAAI 2016
	A Neural Attention Model for Abstractive Sentence Summarization Alexander M. Rush, Sumit Chopra, and Jason Weston. EMNLP 2015.

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