{"paper":{"title":"A Meta-Learning Framework for Multitask Reverberation Mapping in Active Galactic Nuclei","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM"],"primary_cat":"astro-ph.GA","authors_text":"Aman N. Raju, Andjelka B. Kova\\v{c}evi\\'c, {\\DJ}or{\\dj}e Savi\\'c, Dragana Ili\\'c, Eric Slezak, Francesco Tombesi, Iva \\v{C}vorovi\\'c-Hajdinjak, Luka \\v{C}. Popovi\\'c, Marina Pavlovi\\'c, Paula Sanchez-Saez, Sa\\v{s}a Simi\\'c","submitted_at":"2026-06-08T15:48:37Z","abstract_excerpt":"The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to observe active galactic nuclei (AGN) at sky densities of approximately 1000-4000 per sq. deg, enabling photometric reverberation mapping on an unprecedented scale. We present a meta-learning framework for AGN photometric reverberation mapping based on Attentive Latent Neural Processes (ALNP), developed by the SER-SAG-S1 directable software in-kind team for LSST. The framework clusters AGN light curves with similar topologies using Self-Organizing Maps and combines ALNPs with Mixture Density Models to learn ligh"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.09665","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.09665/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}