TACL 2018 paper (presented at ACL 2018) by David Jurgens, Srijan Kumar, Raine Hoover, Daniel A. McFarland, and Daniel Jurafsky

David comes on the podcast to talk to us about citation frames.  We discuss the dataset they created by painstakingly annotating the "citation type" for all of the citations in a large collection of papers (around 2000 citations in total), then training a classifier on that data to annotate the rest of the ACL anthology.  This process itself is interesting, including how exactly the citations are classified, and we talk about this for a bit.  The second half of the podcast talks about the analysis that David and colleagues did using the (automatically) annotated ACL anthology, trying to gauge how the field has changed over time.

https://www.semanticscholar.org/paper/Measuring-the-Evolution-of-a-Scientific-Field-Jurgens-Kumar/65118f3a7463f54bdf9b9e5cdd655953a2488c2f

70 - Measuring the Evolution of a Scientific Field through Citation Frames, with David Jurgens

Welcome to the NLP highlights podcast, where we invite researchers to talk about their work in various areas in natural language processing. All views expressed belong to the hosts/guests, and do not represent their employers.

Science

Are LLMs safe?

This podcast episode features Dr. Mohamed Elhoseiny, a true luminary in the realm of computer vision with over a decade of groundbreaking research. As an Assistant Professor at KAUST, Dr. Elhoseiny's work delves into the intersections of Computer Vision, Language & Vision, and Computational Creativity in Art, Fashion, and AI. Notably, he co-organized the 1st and 2nd Workshops on Closing the Loop between Vision and Language, demonstrating his commitment to advancing interdisciplinary research. With a rich educational background from Stanford University's Graduate School of Business Ignite Program, and Rutgers University as MS/PhD Researcher, coupled with influential stints at Stanford, Baidu Research, Facebook AI Research, Adobe Research, and SRI International, Dr. Elhoseiny brings a wealth of experience to our discussion.

"Imaginative AI" with Mohamed Elhoseiny

Our first guest with this new format is Kyle Lo, the most senior lead scientist in the Semantic Scholar team at Allen Institute for AI (AI2), who kindly agreed to share his perspective on #Science of #Science (#scisci) on our podcast. SciSci is concerned with studying how people do science, and includes developing methods and tools to help people consume AND produce science. Kyle has made several critical contributions in this field which enabled a lot of SciSci work over the past 5+ years, ranging from novel NLP methods (eg, SciBERT https://lnkd.in/gTP_tYiF ), to open data collections (eg, S2ORK https://lnkd.in/g4J6tXCG), to toolkits for manipulating scientific documents (eg, PaperMage https://lnkd.in/gwU7k6mJ which JUST received a Best Paper Award 

142 - Science Of Science, with Kyle Lo

In this special episode of NLP Highlights, we discussed building and open sourcing language models. What is the usual recipe for building large language models? What does it mean to open source them? What new research questions can we answer by open sourcing them? We particularly focused on the ongoing Open Language Model (OLMo) project at AI2, and invited Iz Beltagy and Dirk Groeneveld, the research and engineering leads of the OLMo project to chat.

Blog post announcing OLMo: https://blog.allenai.org/announcing-ai2-olmo-an-open-language-model-made-by-scientists-for-scientists-ab761e4e9b76

Organizations interested in partnership can express their interest here: https://share.hsforms.com/1blFWEWJ2SsysSXFUEJsxuA3ioxm

You can find Iz at twitter.com/i_beltagy and Dirk at twitter.com/mechanicaldirk

141 - Building an open source LM, with Iz Beltagy and Dirk Groeneveld

In this special episode, we chatted with Chris Callison-Burch about his testimony in the recent U.S. Congress Hearing on the Interoperability of AI and Copyright Law. We started by asking Chris about the purpose and the structure of this hearing. Then we talked about the ongoing discussion on how the copyright law is applicable to content generated by AI systems, the potential risks generative AI poses to artists, and Chris’ take on all of this. We end the episode with a recording of Chris’ opening statement at the hearing.

70 - Measuring the Evolution of a Scientific Field through Citation Frames, with David Jurgens

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