Séminaires RALI-OLST

Data-efficient learning with augmentation, evaluation, and collaboration

Bang Liu (bang (point) liu <at> umontreal (point) ca)

RALI, DIRO / MILA

Wednesday 20 October 2021 at 11:30 AM

Réunion Zoom (below)


While existing approaches for question answering (QA) attain state-of-the-art (SOTA) performance when trained with large amounts of data, the ability to learn in a sample-efficient manner is a necessity in data-limited domains. I this talk, I will introduce our recent research on automatic question generation (QG) and question answering. Specifically, creating a high-quality question answering dataset for different domains is an extremely time-consuming and laborious task. To solve this issue, we propose to reduce the labeling cost and improve learning efficiency by automatically generating large-scale, high-quality QA pairs, evaluating the quality of the generated data and the ability of the trained model, and designing efficient strategies to collaboratively improving correlated tasks, such as question answering and question generation.

Recording: https://drive.google.com/file/d/1s6YHEkxBtfXerdH0McVCaXtK2PTZtnQr/view?usp=sharing



Join with Zoom at this url.
Meeting ID: 916 9097 5818, 𝑷𝒂𝒔𝒔𝒄𝒐𝒅𝒆: 343273.
Phone numbers: https://umontreal.zoom.us/u/abitNZzLg.
One tap mobile: +14388097799,,91690975818#,,,,,,0#,,343273#


To receive weekly talk announcements, please send an e-mail to majordomo@iro.umontreal.ca. Simply write a message containing the single line 'subscribe ralli' (without the quotes, with a double 'l' in 'ralli').

See all the weekly talks for the year:

1991 1992 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022