{"paper":{"title":"Submodular Welfare Maximization with Budget Constraints in the Random-Order Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Martin Knaack, Max Klimm","submitted_at":"2026-06-21T14:19:48Z","abstract_excerpt":"We study an online item-allocation problem with budgets and a submodular objective. A set of $m$ agents is known in advance, and each agent $j$ has a known budget. A set of $n$ items arrives over time in a uniformly random order. When item $i$ arrives, its cost $c_{i,j}$ for each agent $j$ is revealed, and the algorithm must irrevocably assign $i$ to an agent without violating any budget constraint. The goal is to maximize a monotone submodular function defined over all possible assignments $[n] \\times [m]$. At the time of decision, the algorithm has only oracle access to this submodular funct"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.22520","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/2606.22520/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"}