{"paper":{"title":"Semi-Streaming Algorithms for Submodular Maximization under Random Arrival Order","license":"http://creativecommons.org/licenses/by/4.0/","headline":"Random arrival order enables semi-streaming algorithms to achieve better approximations than adversarial order for submodular maximization under matroid constraints.","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Moran Feldman, Niv Buchbinder, Sherry Sarkar, Siyue Liu","submitted_at":"2026-05-14T02:56:24Z","abstract_excerpt":"We study random order semi-streaming algorithms for submodular maximization under a wide range of combinatorial constraint classes, including matroids, matroid $p$-parity, $p$-exchange systems and $p$-systems. For most of these classes of constraints, our results are the first improvement over what is known to be achievable for adversarial order. For matroids, matching and $p$-matchoids, previous random order results were known, and we improve over some of these as well. In the case of matroids, our improved results show a separation between adversarial and random order semi-streaming algorith"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"For matroids our improved results show a separation between adversarial and random order semi-streaming algorithms, and exponentially improve the number of passes necessary for getting 1-1/e-ε approximation.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The arrival order is drawn uniformly at random from all permutations; if the order is only approximately random or has hidden correlations the stated guarantees may not hold.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"New random-order semi-streaming algorithms improve approximation guarantees over adversarial-order results for submodular maximization under matroids and related constraints, with an exponential reduction in passes needed for near-optimal matroid results.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Random arrival order enables semi-streaming algorithms to achieve better approximations than adversarial order for submodular maximization under matroid constraints.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"9b2546ba802fa50545abcf7e383854098ac57b20c9bffdbc25ee43b00b28bd9b"},"source":{"id":"2605.14296","kind":"arxiv","version":1},"verdict":{"id":"cecc6ee1-6e32-41e6-9e4b-33beac4055d8","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-15T02:23:31.956116Z","strongest_claim":"For matroids our improved results show a separation between adversarial and random order semi-streaming algorithms, and exponentially improve the number of passes necessary for getting 1-1/e-ε approximation.","one_line_summary":"New random-order semi-streaming algorithms improve approximation guarantees over adversarial-order results for submodular maximization under matroids and related constraints, with an exponential reduction in passes needed for near-optimal matroid results.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The arrival order is drawn uniformly at random from all permutations; if the order is only approximately random or has hidden correlations the stated guarantees may not hold.","pith_extraction_headline":"Random arrival order enables semi-streaming algorithms to achieve better approximations than adversarial order for submodular maximization under matroid constraints."},"references":{"count":300,"sample":[{"doi":"","year":null,"title":"Niv Buchbinder and Moran Feldman , title =","work_id":"fc7503c2-3352-411e-b422-686b5878967b","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"Nguyen and Andrew Suh , title =","work_id":"9fea2415-e32f-441d-a430-9a3dc08e0102","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"Streaming Submodular Maximization Under Matroid Constraints , booktitle = proc #","work_id":"1f156834-4622-4553-8dbe-b8c57f8ff598","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"The one-way communication complexity of submodular maximization with applications to streaming and robustness , booktitle = proc #","work_id":"bb2df97c-30b5-4fc3-8eaa-878e9740541f","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":null,"title":"Ehsan Kazemi and Marko Mitrovic and Morteza Zadimoghaddam and Silvio Lattanzi and Amin Karbasi , title =","work_id":"0f77c598-fc77-425b-9815-d61b6abe6849","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":300,"snapshot_sha256":"314b437ae5b8a0a71749e8529f1a0bb008d177cbf35c144a9ecdb04183b119a5","internal_anchors":5},"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"}