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UID:pretalx-adass2026-WUYEGC@pretalx.adass.org
DTSTART;TZID=AWST:20261102T161500
DTEND;TZID=AWST:20261102T163000
DESCRIPTION:Generating database queries from natural language remains a cha
 llenging task\, particularly in specialized scientific domains. In this wo
 rk\, we study natural language to Astronomical Data Query Language (ADQL) 
 generation using large language models (LLMs). We curate a high-quality da
 taset of natural language–ADQL pairs through an LLM-assisted filtering a
 nd validation pipeline and use it to fine-tune models of varying sizes and
  capabilities. To enable systematic evaluation\, we construct an expert-an
 notated benchmark of queries for the Gaia mission\, spanning a range of qu
 ery complexities\, from simple retrieval tasks to complex joins and aggreg
 ations. Finally\, we compare fine-tuned models against retrieval-augmented
  generation (RAG) approaches\, analyzing their effectiveness in terms of q
 uery correctness and robustness. Our results provide insights into the rel
 ative strengths of fine-tuning and retrieval augmentation for domain-speci
 fic scientific query generation.
DTSTAMP:20261015T123813Z
LOCATION:Banquet Hall
SUMMARY:ADQL generation using LLMs - Sandor Kruk
URL:https://pretalx.adass.org/adass2026/talk/WUYEGC/
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UID:pretalx-adass2026-WP89MK@pretalx.adass.org
DTSTART;TZID=AWST:20261104T173000
DTEND;TZID=AWST:20261104T183000
DESCRIPTION:Astronomy is entering an era in which several major facilities 
 are simultaneously operating\, or standing up\, science platforms designed
  to deliver petabyte-scale data and computing to their communities. As mis
 sions and observatories move from data collection to data delivery at scal
 e\, they are independently converging on similar architectural choices —
  and independently running into similar operational challenges — around 
 federated access\, compute-to-data\, authentication\, and long-term sustai
 nability. This BoF is proposed by confirmed panelists from Euclid/ESA Data
 labs\, Vera Rubin Observatory\, the SKA Regional Centre Network (SRCNet)\,
  Roman Telescope\, CADC/CANFAR\, NASA/Fornax and LOFAR. Other platforms ar
 e invited to join the discussion to compare architectures\, operational le
 ssons\, and user-facing services for large-scale science platforms and wor
 kflows.\n\nWith Euclid's Data Release 1 (DR1)\, a full year of Vera Rubin 
 Observatory operations\, the launch of the Roman Space Telescope\, and SKA
  Low's science verification getting underway next year\, the timing is ide
 al to take stock of what's working\, what isn't\, and where the community 
 could converge — on topics such as federated data access\, compute-to-da
 ta models\, interoperability standards\, and the balance between bespoke p
 latform development and shared infrastructure. Panellists will open the se
 ssion with a short position statement on how their platform is architected
  and operated today\, before the floor opens to a moderated discussion aim
 ed at surfacing common challenges and concrete opportunities for collabora
 tion across observatories.
DTSTAMP:20261015T123813Z
LOCATION:Seminar Room 1
SUMMARY:Science Platforms at Scale: Developing Data Services in the Petabyt
 e Era - Javier Ballester Arenas\, Yan Grange\, Marcos López-Caniego\, San
 dor Kruk\, Jesus Salgado\, Christophe Arviset\, Michele Delli Veneri\, Ros
 ie Bolton\, William O Mullane\, Carmen Toribio\, Brian Major
URL:https://pretalx.adass.org/adass2026/talk/WP89MK/
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