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BEGIN:VEVENT
SUMMARY:Deep Learning students tackle online hate speech - Poster Session 
 on 27 May
DTSTART:20260527T083000
DTEND:20260527T133000
DTSTAMP:20260526T230541Z
UID:19484c4865b687b46d3aacf6fd35014457c50d343b7b759f55a69447
CATEGORIES:Conferences - Seminars
DESCRIPTION:Students who attended the Deep Learning course EE-559\nStudent
 s in the Deep Learning course will showcase their group projects focused o
 n fostering safer online spaces. The poster session will highlight their d
 eep learning models designed to identify and address hate speech across a 
 variety of online content.\n\nThe group projects tackle online hate in its
  diverse forms\, ranging from text to images\, memes\, videos\, and audio 
 content. With the objective of creating healthier online interactions\, th
 e students designed their models to prioritize both accuracy and a nuanced
  understanding of context in order to distinguish between genuinely harmfu
 l hate speech and legitimate critical discourse or satirical expression.\n
 \nThe development of these deep learning models aims to prevent the prolif
 eration of hateful rhetoric\, ultimately contributing to a more respectful
  online environment where diverse voices can coexist and thrive.
LOCATION:MED hall https://plan.epfl.ch/?room==MED%200%2094.22
STATUS:CONFIRMED
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