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-22380@www.clsp.jhu.edu DTSTAMP:20240328T180143Z 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-23306@www.clsp.jhu.edu DTSTAMP:20240328T180143Z CATEGORIES;LANGUAGE=en-US:Seminars CONTACT: DESCRIPTION:
Abstract
\nWhile large language model s have advanced the state-of-the-art in natural language processing\, thes e models are trained on large-scale datasets\, which may include harmful i nformation. Studies have shown that as a result\, the models exhibit socia l biases and generate misinformation after training. In this talk\, I will discuss my work on analyzing and interpreting the risks of large language models across the areas of fairness\, trustworthiness\, and safety. I wil l first describe my research in the detection of dialect bias between Afri can American English (AAE) vs. Standard American English (SAE). The second part investigates the trustworthiness of models through the memorization and subsequent generation of conspiracy theories. I will end my talk with recent work in AI safety regarding text that may lead to physical harm.
\nBiography
\nSharon is a 5th-year Ph.D. candid ate at the University of California\, Santa Barbara\, where she is advised by Professor William Wang. Her research interests lie in natural language processing\, with a focus on Responsible AI. Sharon’s research spans the subareas of fairness\, trustworthiness\, and safety\, with publications in ACL\, EMNLP\, WWW\, and LREC. She has spent summers interning at AWS\, Me ta\, and Pinterest. Sharon is a 2022 EECS Rising Star and a current recipi ent of the Amazon Alexa AI Fellowship for Responsible AI.
DTSTART;TZID=America/New_York:20230206T120000 DTEND;TZID=America/New_York:20230206T131500 LOCATION:Hackerman Hall B17 @ 3400 N. Charles Street\, Baltimore\, MD 21218 SEQUENCE:0 SUMMARY:Sharon Levy (University of California\, Santa Barbara) “Responsible AI via Responsible Large Language Models” URL:https://www.clsp.jhu.edu/events/sharon-levy-university-of-california-sa nta-barbara-responsible-ai-via-responsible-large-language-models/ X-COST-TYPE:free X-TAGS;LANGUAGE=en-US:2023\,February\,Levy END:VEVENT END:VCALENDAR