BEGIN:VCALENDAR VERSION:2.0 PRODID:-//UC Irvine//CML Seminars//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Towards Transparent Language Models X-WR-TIMEZONE:America/Los_Angeles BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20070311T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20071104T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:2023-10-23-sarah-wiegreffe@cml.ics.uci.edu DTSTAMP:20231023T000000Z SEQUENCE:57690 DTSTART;TZID=America/Los_Angeles:20231023T130000 DTEND;TZID=America/Los_Angeles:20231023T140000 SUMMARY:[CML Seminar] Sarah Wiegreffe: Towards Transparent Language Models LOCATION:Donald Bren Hall 4011 DESCRIPTION:Sarah Wiegreffe\, Postdoctoral Researcher\, Allen Institute for AI and University of Washington\n\nTitle: Towards Transparent Language Mo dels\n\nAbstract: Recently-released language models have attracted a lot o f attention for their major successes and (often more subtle\, but still p lentiful) failures. In this talk\, I will motivate why transparency into m odel operations is needed to rectify these failures and increase model uti lity in a reliable way. I will highlight how techniques must be developed in this changing NLP landscape for both open-source models and black-box m odels behind an API. I will provide an example of each from my recent work demonstrating how improved transparency can improve language model perfor mance on downstream tasks.\n\nhttps://cml.ics.uci.edu/seminars/2023-10-23- sarah-wiegreffe X-ALT-DESC;FMTTYPE=text/html:Sarah Wiegreffe\, Postdocto ral Researcher\, Allen Institute for AI and University of Washington
Title: Towards Transparent Language Models

Abstract: Recently-released language models have attracted a lot of attention for their major successes and (often more subtle\, but still plentiful) failur es. In this talk\, I will motivate why transparency into model operations is needed to rectify these failures and increase model utility in a reliab le way. I will highlight how techniques must be developed in this changing NLP landscape for both open-source models and black-box models behind an API. I will provide an example of each from my recent work demonstrating h ow improved transparency can improve language model performance on downstr eam tasks.

https://cml.ics.uci.edu/seminars/2023-10-23-sarah-wiegreffe< /a> URL:https://cml.ics.uci.edu/seminars/2023-10-23-sarah-wiegreffe END:VEVENT END:VCALENDAR