{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:YFNBY5RI2HA7HSQVD42CYN4P36","short_pith_number":"pith:YFNBY5RI","schema_version":"1.0","canonical_sha256":"c15a1c7628d1c1f3ca151f342c378fdf9ce0c928e36c2cedb5ecedbe7d5d63a6","source":{"kind":"arxiv","id":"1705.02748","version":2},"attestation_state":"computed","paper":{"title":"Computing an Approximately Optimal Agreeable Set of Items","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Pasin Manurangsi, Warut Suksompong","submitted_at":"2017-05-08T05:31:17Z","abstract_excerpt":"We study the problem of finding a small subset of items that is \\emph{agreeable} to all agents, meaning that all agents value the subset at least as much as its complement. Previous work has shown worst-case bounds, over all instances with a given number of agents and items, on the number of items that may need to be included in such a subset. Our goal in this paper is to efficiently compute an agreeable subset whose size approximates the size of the smallest agreeable subset for a given instance. We consider three well-known models for representing the preferences of the agents: ordinal prefe"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1705.02748","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2017-05-08T05:31:17Z","cross_cats_sorted":[],"title_canon_sha256":"2d62acf16b6931b9bf2fc4efc7aa9fb3dc9ee5fb7cf77ea5019901bae204fd62","abstract_canon_sha256":"d3d76b72f662e4261fa7900a72769a4664a276fba2c630ffae5945b82d6d5b6c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:54:48.750272Z","signature_b64":"pTWgXWx5YXhzBXihlONc+iauRi7/urQRQC0H+aS15ZPOFdbyTkzsQOzkPwrleQJTpSo1l6Crq03ducGL1mK8CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c15a1c7628d1c1f3ca151f342c378fdf9ce0c928e36c2cedb5ecedbe7d5d63a6","last_reissued_at":"2026-05-17T23:54:48.749697Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:54:48.749697Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Computing an Approximately Optimal Agreeable Set of Items","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Pasin Manurangsi, Warut Suksompong","submitted_at":"2017-05-08T05:31:17Z","abstract_excerpt":"We study the problem of finding a small subset of items that is \\emph{agreeable} to all agents, meaning that all agents value the subset at least as much as its complement. Previous work has shown worst-case bounds, over all instances with a given number of agents and items, on the number of items that may need to be included in such a subset. Our goal in this paper is to efficiently compute an agreeable subset whose size approximates the size of the smallest agreeable subset for a given instance. We consider three well-known models for representing the preferences of the agents: ordinal prefe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.02748","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1705.02748","created_at":"2026-05-17T23:54:48.749800+00:00"},{"alias_kind":"arxiv_version","alias_value":"1705.02748v2","created_at":"2026-05-17T23:54:48.749800+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.02748","created_at":"2026-05-17T23:54:48.749800+00:00"},{"alias_kind":"pith_short_12","alias_value":"YFNBY5RI2HA7","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_16","alias_value":"YFNBY5RI2HA7HSQV","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_8","alias_value":"YFNBY5RI","created_at":"2026-05-18T12:31:56.362134+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YFNBY5RI2HA7HSQVD42CYN4P36","json":"https://pith.science/pith/YFNBY5RI2HA7HSQVD42CYN4P36.json","graph_json":"https://pith.science/api/pith-number/YFNBY5RI2HA7HSQVD42CYN4P36/graph.json","events_json":"https://pith.science/api/pith-number/YFNBY5RI2HA7HSQVD42CYN4P36/events.json","paper":"https://pith.science/paper/YFNBY5RI"},"agent_actions":{"view_html":"https://pith.science/pith/YFNBY5RI2HA7HSQVD42CYN4P36","download_json":"https://pith.science/pith/YFNBY5RI2HA7HSQVD42CYN4P36.json","view_paper":"https://pith.science/paper/YFNBY5RI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1705.02748&json=true","fetch_graph":"https://pith.science/api/pith-number/YFNBY5RI2HA7HSQVD42CYN4P36/graph.json","fetch_events":"https://pith.science/api/pith-number/YFNBY5RI2HA7HSQVD42CYN4P36/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YFNBY5RI2HA7HSQVD42CYN4P36/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YFNBY5RI2HA7HSQVD42CYN4P36/action/storage_attestation","attest_author":"https://pith.science/pith/YFNBY5RI2HA7HSQVD42CYN4P36/action/author_attestation","sign_citation":"https://pith.science/pith/YFNBY5RI2HA7HSQVD42CYN4P36/action/citation_signature","submit_replication":"https://pith.science/pith/YFNBY5RI2HA7HSQVD42CYN4P36/action/replication_record"}},"created_at":"2026-05-17T23:54:48.749800+00:00","updated_at":"2026-05-17T23:54:48.749800+00:00"}