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VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:Deep Learning students tackle online hate speech - Poster Session 
 on 28 May
DTSTART:20250528T083000
DTEND:20250528T133000
DTSTAMP:20260315T145242Z
UID:b763b3add9beafce321fbb28decea6c6132a73663fb31022d1763595
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=%3DMED%200%2094.22&dim_floor=
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 layers_mobilite_acces_grp=metro&tree_group_layers_restauration_et_commerce
 s_grp=&tree_group_layers_enseignement=guichet_etudiants&tree_group_layers_
 services_campus_grp=information_epfl&tree_group_layers_equipements_grp=&ba
 selayer_ref=grp_backgrounds&map_x=2533110&map_y=1152397&map_zoom=12
STATUS:CONFIRMED
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