NLP in the Wild: From Ancient Akkadian to Biochemistry Protocols
We are excited to start our NLP seminar this week! Our first speaker for the semester is Dr. Gabriel Stanovsky, a senior lecturer (≈ assistant professor) at the Hebrew University of Jerusalem.
Time: 01/29/2021, 12.30pm - 1.30pm
Title: NLP in the Wild: From Ancient Akkadian to Biochemistry Protocols
I’ll present two recent projects showing the range of domains I’d like to tackle in my work to help experts with diverse real-world research questions. First, I’ll present a model capable of filling in missing parts in ancient cuneiform tablets written thousands of years ago in now-extinct languages (Akkadian and Sumerian). Due to deterioration over time, these excavated tablets are often broken, faded, or cracked, making it hard for historians and archaeologists to read and interpret them. We show that by leveraging large-scale language models pretrained on modern texts we achieve good results in restoring missing parts in various domains and time periods, in the automatic evaluation as well as human analysis. Second, I will discuss a novel document-level representation of wet lab biochemistry protocols geared towards experiment automation and reproducibility, addressing challenges such as cross-sentence relations, long-range coreference, grounding, and implicit arguments. I’ll show examples from a manually-annotated corpus of complex lab protocols, and present graph-prediction models that form the first step towards fully executable lab protocols.
Dr. Gabriel Stanovsky is a senior lecturer (≈ assistant professor) at the Hebrew University of Jerusalem. He did his postdoctoral research at the University of Washington and the Allen Institute for AI in Seattle, working with Prof. Luke Zettlemoyer and Prof. Noah Smith, and his PhD with Prof. Ido Dagan at Bar-Ilan University. He is interested in developing NLP models that with benefits for users in real-world applications. His work has received awards at top-tier conferences, including ACL and CoNLL, and recognition in popular journals such as Science and The New York Times.
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