BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//wp-events-plugin.com//7.2.3.1//EN
BEGIN:VEVENT
UID:767@lincs.fr
DTSTART;TZID=Europe/Paris:20230510T150000
DTEND;TZID=Europe/Paris:20230510T160000
DTSTAMP:20230526T082147Z
URL:https://www.lincs.fr/events/talk-jerome-ramos/
SUMMARY:Quantifying the Bias of Transformer-Based Language Models for
 African American English in Masked Language Modeling
DESCRIPTION:\n\nIn recent years\, groundbreaking transformer-based language
 models (LMs) have made tremendous advances in natural language processing
 (NLP) tasks. However\, the measurement of their fairness with respect to
 different social groups still remains unsolved. In this paper\, we propose
 and thoroughly validate an evaluation technique to assess the quality and
 bias of language model predictions on transcripts of both spoken African
 American English (AAE) and Spoken American English (SAE). Our analysis
 reveals the presence of a bias towards SAE encoded by state-of-the-art LMs
 such as BERT and DistilBERT and a lower bias in distilled LMs. We also
 observe a bias towards AAE in RoBERTa and BART. Additionally\, we show
 evidence that this disparity is present across all the LMs when we only
 consider the grammar and the syntax specific to AAE.\nShort bio:\nJerome
 Ramos is a second year PhD student at University College London supervised
 by Dr. Aldo Lipani. His research interests include explainability and
 scrutability in conversational recommender systems.\n
CATEGORIES:Seminars,Youtube
LOCATION:Room 4B01\, 19 place Marguerite Perey\, Palaiseau\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=19 place Marguerite Perey\,
 Palaiseau\, France;X-APPLE-RADIUS=100;X-TITLE=Room 4B01:geo:0,0
END:VEVENT
BEGIN:VTIMEZONE
TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
BEGIN:DAYLIGHT
DTSTART:20230326T030000
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
END:DAYLIGHT
END:VTIMEZONE
END:VCALENDAR