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DTSTART;VALUE=DATE:20260427
DTEND;VALUE=DATE:20260428
DTSTAMP:20260423T100947
CREATED:20260121T215144Z
LAST-MODIFIED:20260402T165134Z
UID:8026-1777248000-1777334399@tilos.ai
SUMMARY:ICLR 2026 Workshop: Principled Design for Trustworthy AI - Interpretability\, Robustness\, and Safety across Modalities
DESCRIPTION:Modern AI systems\, particularly large language models\, vision-language models\, and deep vision networks\, are increasingly deployed in high-stakes settings such as healthcare\, autonomous driving\, and legal decisions. Yet\, their lack of transparency\, fragility to distributional shifts between train/test environments\, and representation misalignment in emerging tasks and data/feature modalities raise serious concerns about their trustworthiness. \nThis workshop focuses on developing trustworthy AI systems by principled design: models that are interpretable\, robust\, and aligned across the full lifecycle – from training and evaluation to inference-time behavior and deployment. We aim to unify efforts across modalities (language\, vision\, audio\, and time series) and across technical areas of trustworthiness spanning interpretability\, robustness\, uncertainty\, and safety.
URL:https://tilos.ai/event/iclr-2026-workshop-principled-design-for-trustworthy-ai-interpretability-robustness-and-safety-across-modalities/
LOCATION:ICLR 2026\, Riocentro Convention and Event Center\, Rio de Janiero\, Brazil
CATEGORIES:TILOS Sponsored Event,Workshop
ATTACH;FMTTYPE=image/jpeg:https://tilos.ai/wp-content/uploads/2026/01/rio.jpg
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