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UID:pretalx-pyconde-pydata-2025-F9EFXA@pretalx.com
DTSTART;TZID=CET:20250423T175000
DTEND;TZID=CET:20250423T182000
DESCRIPTION:Despite an array of regulations implemented by governments and 
 social media platforms worldwide (i.e. famous DSA)\, the problem of digita
 l abusive speech persists. At the same time\, rapid advances in NLP and la
 rge language models (LLMs) are opening up new possibilities—and responsi
 bilities—for using this technology to make a positive social impact. Can
  LLMs streamline content moderation efforts? Are they effective at spottin
 g and countering hate speech\, and can they help produce more proactive so
 lutions like text detoxification and counter-speech generation?\n\nIn this
  talk\, we will dive into the cutting-edge research and best practices of 
 automatic textual content moderation today. From clarifying core definitio
 ns to detailing actionable methods for leveraging multilingual NLP models\
 , we will provide a practical roadmap for researchers\, developers\, and p
 olicymakers aiming to tackle the challenges of harmful online content. Joi
 n us to discover how modern NLP can foster safer\, more inclusive digital 
 communities.
DTSTAMP:20260423T000937Z
LOCATION:Hassium
SUMMARY:Modern NLP for Proactive Harmful Content Moderation - Daryna Dement
 ieva
URL:https://pretalx.com/pyconde-pydata-2025/talk/F9EFXA/
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