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UID:pretalx-openalt-2026-V9JLZU@talks.openalt.cz
DTSTART;TZID=CET:20261107T160000
DTEND;TZID=CET:20261107T162500
DESCRIPTION:Updating a specific fact in a 70-billion-parameter model usuall
 y feels like using a sledgehammer for heart surgery. Traditional retrainin
 g is slow and expensive\, often breaking unrelated behaviors in the proces
 s. ROME (Rank-One Model Editing) offers a more surgical alternative\, trea
 ting model weights like a database that can be precisely updated without a
  full rebuild.\nThis talk is ongoing collaborative research between Red Ha
 t and FIT BUT into the world of AI forensics. Our focus is the security si
 de of model editing: if a fact can be patched in seconds\, it can just as 
 easily be poisoned\, quietly and without obvious traces. We move past the 
 black box mystery to show how we can locate where a specific fact lives wi
 thin a transformer's architecture. We will explore the mechanics of knowle
 dge neurons\, the risk of unintended side effects like hallucinations\, an
 d the serious security implications of malicious fact injections or stealt
 h patching. Through demonstration using our open-source toolkit\, we will 
 show how ROME performs precision strikes on state-of-the-art models\, high
 lighting both its efficiency and the scenarios where the method’s assump
 tions break down. We close by presenting our prototype for detecting edite
 d models\, a first step toward catching tampered weights before they reach
  production.
DTSTAMP:20261030T174240Z
LOCATION:D0207
SUMMARY:Surgery on a Brain: Live-Patching Facts in LLMs with ROME - Jakub R
 eš
URL:https://talks.openalt.cz/openalt-2026/talk/V9JLZU/
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