BEGIN:VCALENDAR VERSION:2.0 PRODID:-//128.220.36.25//NONSGML kigkonsult.se iCalcreator 2.26.9// CALSCALE:GREGORIAN METHOD:PUBLISH X-FROM-URL:https://www.clsp.jhu.edu X-WR-TIMEZONE:America/New_York BEGIN:VTIMEZONE TZID:America/New_York X-LIC-LOCATION:America/New_York BEGIN:STANDARD DTSTART:20231105T020000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RDATE:20241103T020000 TZNAME:EST END:STANDARD BEGIN:DAYLIGHT DTSTART:20240310T020000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RDATE:20250309T020000 TZNAME:EDT END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:ai1ec-20716@www.clsp.jhu.edu DTSTAMP:20240329T103533Z CATEGORIES;LANGUAGE=en-US:Seminars CONTACT: DESCRIPTION:
Abstract
\nOver the last few years\, deep neural models have taken over the field of natural language processin g (NLP)\, brandishing great improvements on many of its sequence-level tas ks. But the end-to-end nature of these models makes it hard to figure out whether the way they represent individual words aligns with how language b uilds itself from the bottom up\, or how lexical changes in register and d omain can affect the untested aspects of such representations.
\nIn this talk\, I will present NYTWIT\, a dataset created to challenge large l anguage models at the lexical level\, tasking them with identification of processes leading to the formation of novel English words\, as well as wit h segmentation and recovery of the specific subclass of novel blends. I wi ll then present XRayEmb\, a method which alleviates the hardships of proce ssing these novelties by fitting a character-level encoder to the existing models’ subword tokenizers\; and conclude with a discussion of the drawba cks of current tokenizers’ vocabulary creation schemes.
\nBi ography
\nYuval Pinter is a Senior Lecturer in the Department of Comp uter Science at Ben-Gurion University of the Negev\, focusing on natural l anguage processing. Yuval got his PhD at t he Georgia Institute of Technology School of Interactive Computing as a Bl oomberg Data Science PhD Fellow. Before that\, he worked as a Research Eng ineer at Yahoo Labs and as a Computational Linguist at Ginger Software\, a nd obtained an MA in Linguistics and a BSc in CS and Mathematics\, both fr om Tel Aviv University. Yuval blogs (in He brew) about language matters on Dagesh Kal.
DTSTART;TZID=America/New_York:20210910T120000 DTEND;TZID=America/New_York:20210910T131500 LOCATION:Hackerman Hall B17 @ 3400 N. Charles Street\, Baltimore\, MD SEQUENCE:0 SUMMARY:Yuval Pinter (Ben-Gurion University – Virtual Visit) “Challenging a nd Adapting NLP Models to Lexical Phenomena” URL:https://www.clsp.jhu.edu/events/yuval-pinter/ X-COST-TYPE:free X-TAGS;LANGUAGE=en-US:2021\,Pinter\,September END:VEVENT BEGIN:VEVENT UID:ai1ec-22380@www.clsp.jhu.edu DTSTAMP:20240329T103533Z CATEGORIES;LANGUAGE=en-US:Seminars CONTACT: DESCRIPTION:Abstract
\nThe availability of large multilingual pre-trained language models has opened up exciting pathways f or developing NLP technologies for languages with scarce resources. In thi s talk I will advocate for the need to go beyond the most common languages in multilingual evaluation\, and on the challenges of handling new\, unse en-during-training languages and varieties. I will also share some of my e xperiences with working with indigenous and other endangered language comm unities and activists.
\nBiography
\nAntonios Anastasopoulos is an As sistant Professor in Computer Science at George Mason University. In 2019\ , Antonis received his PhD in Computer Science from the University of Notr e Dame and then worked as a postdoctoral researcher at the Language Techno logies Institute at Carnegie Mellon University. His research interests rev olve around computational linguistics and natural language processing with a focus on low-resource settings\, endangered languages\, and cross-lingu al learning.
\nDTSTART;TZID=America/New_York:20220930T120000 DTEND;TZID=America/New_York:20220930T131500 LOCATION:Hackerman Hall B17 @ 3400 N. Charles Street\, Baltimore\, MD 21218 SEQUENCE:0 SUMMARY:Antonios Anastasopoulos (George Mason University) “NLP Beyond the T op-100 Languages” URL:https://www.clsp.jhu.edu/events/antonis-anastasopoulos-george-mason-uni versity/ X-COST-TYPE:free X-TAGS;LANGUAGE=en-US:2022\,Anastasopoulos\,September END:VEVENT BEGIN:VEVENT UID:ai1ec-23894@www.clsp.jhu.edu DTSTAMP:20240329T103533Z CATEGORIES;LANGUAGE=en-US:Seminars CONTACT: DESCRIPTION:
Abstract
\nThe use of NLP in the real m of financial technology is broad and complex\, with applications ranging from sentiment analysis and named entity recognition to question answerin g. Large Language Models (LLMs) have been shown to be effective on a varie ty of tasks\; however\, no LLM specialized for the financial domain has be en reported in the literature. In this work\, we present BloombergGPT\, a 50 billion parameter language model that is trained on a wide range of fin ancial data. We construct a 363 billion token dataset based on Bloomberg’s extensive data sources\, perhaps the largest domain-specific dataset yet\ , augmented with 345 billion tokens from general-purpose datasets. We val idate BloombergGPT on standard LLM benchmarks\, open financial benchmarks\ , and a suite of internal benchmarks that most accurately reflect our inte nded usage. Our mixed dataset training leads to a model that outperforms e xisting models on financial tasks by significant margins without sacrifici ng performance on general LLM benchmarks. Additionally\, we explain our mo deling choices\, training process\, and evaluation methodology.
\nBiography
Mark Dredze is the John C Malone Professo r of Computer Science at Johns Hopkins University and the Director of Rese arch (Foundations of AI) for the JHU AI-X Foundry. He develops Artificial Intelligence Systems based on natural language processing and explores app lications to public health and medicine.
\nProf. Dredze is affiliate d with the Malone Center for Engineering in Healthcare\, the Center for La nguage and Speech Processing\, among others. He holds a joint appointment in the Biomedical Informatics & Data Science Section (BIDS)\, under the Depart ment of Medicine (DOM)\, Division of General Internal Medicine (GIM) in th e School of Medicine. He obtained his PhD from the University of Pennsylva nia in 2009.
DTSTART;TZID=America/New_York:20230918T120000 DTEND;TZID=America/New_York:20230918T131500 LOCATION:Hackerman Hall B17 @ 3400 N. Charles Street\, Baltimore\, MD 21218 SEQUENCE:0 SUMMARY:Mark Dredze (Johns Hopkins University) “BloombergGPT: A Large Langu age Model for Finance” URL:https://www.clsp.jhu.edu/events/mark-dredze-johns-hopkins-university/ X-COST-TYPE:free X-TAGS;LANGUAGE=en-US:2023\,Dredze\,September END:VEVENT END:VCALENDAR