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CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260915T162040Z
DTSTART:20261014T100000Z
DTEND:20261014T110000Z
SUMMARY:AI Fun with ELLIS Invited Speaker Series | Jin Zhu
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}d3d-mu2vokm
 8-l44yq
DESCRIPTION:Our invited speaker on 14 October will be Jin Zhu from the Un
 iversity of Birmingham.\n\nTitle: Statistics-Powered Detection of LLM-Ge
 nerated Text\n\nAbstract: Large language models (LLMs) such as ChatGPT\,
  Gemini\, and Claude enable the rapid and large-scale generation of huma
 n-like text. Their impact is everywhere\, from education and academia to
  professional work and everyday life. Despite these benefits\, the wides
 pread deployment of LLMs also raises concerns about misinformation\, aca
 demic dishonesty\, and the integrity of digital content. As a result\, d
 etecting LLM-generated text has become an active research topic in machi
 ne learning over the past few years. However\, statistical perspectives 
 on this problem remain largely underexplored. In this talk\, I will pres
 ent several of my recent works on developing statistical methods for det
 ecting LLM-generated text\, with the aim of providing principled and eff
 icient tools for identifying such content. The talk will cover methods p
 resented at recent machine learning conferences\, including NeurIPS and 
 ICLR. An interactive demonstration of one of the proposed methods is ava
 ilable at https://huggingface.co/spaces/stats-powered-ai/StatDetectLLM [
 huggingface.co] \n\nBio: Dr Jin Zhu is an Assistant Professor in the Sch
 ool of Mathematics at the University of Birmingham. His research focuses
  on large language models\, reinforcement learning\, and high-dimensiona
 l data\, particularly on developing computationally efficient methods wi
 th statistical guarantees.\n\nIf you are unable to attend in person\, pl
 ease register via the Ticketsource link provided and you will receive de
 tails for joining via Teams.\n
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:Altas (and Mercury)\, Kilburn Building\, Manchester
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