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UID:pretalx-scipy-2026-SEYACQ@pretalx.com
DTSTART;TZID=CST:20260715T152500
DTEND;TZID=CST:20260715T155500
DESCRIPTION:Scientific breakthroughs don’t happen in plain text\, they li
 ve inside multi-column research papers\, dense data tables\, and intricate
  simulation diagrams. Yet the moment standard AI and Retrieval-Augmented G
 eneration (RAG) pipelines encounter these layouts\, they fail. Tables are 
 flattened into meaningless strings. Figures are ignored. The structural si
 gnals that drive scientific reasoning disappear.\n\nIn this talk\, we show
  how to rescue scientific knowledge from the “text-flattening” trap us
 ing _Docling_\, an open-source document understanding library designed to 
 preserve layout\, hierarchy\, and element boundaries. Instead of reducing 
 everything to text\, we treat tables\, figures\, and sections as first-cla
 ss data structures. Attendees will experience a live demo of a realistic s
 cientific R&D workflow: uploading multiple dense technical PDFs\, executin
 g cross-document natural language queries\, and successfully retrieving sy
 nthesized insights from text\, structured tables\, and scientific images
DTSTAMP:20260715T023004Z
LOCATION:Memorial Hall
SUMMARY:Docling for Multimodal Retrieval - Mahima Arora\, Aarti Jha
URL:https://pretalx.com/scipy-2026/talk/SEYACQ/
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