{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:WQTOUHCD3RVESJG4LAULAOJF7O","short_pith_number":"pith:WQTOUHCD","schema_version":"1.0","canonical_sha256":"b426ea1c43dc6a4924dc5828b03925fbbcbeb12c1b50b79cfbe61d1b3b23d177","source":{"kind":"arxiv","id":"1707.08238","version":2},"attestation_state":"computed","paper":{"title":"A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.DS","authors_text":"Jieming Mao, Xi Chen, Yuanzhi Li","submitted_at":"2017-07-25T22:03:21Z","abstract_excerpt":"We study the active learning problem of top-$k$ ranking from multi-wise comparisons under the popular multinomial logit model. Our goal is to identify the top-$k$ items with high probability by adaptively querying sets for comparisons and observing the noisy output of the most preferred item from each comparison. To achieve this goal, we design a new active ranking algorithm without using any information about the underlying items' preference scores. We also establish a matching lower bound on the sample complexity even when the set of preference scores is given to the algorithm. These two res"},"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":"1707.08238","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2017-07-25T22:03:21Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"a4ff96336100b0132dc65b658f036b49da9a43f32bd4585c8781e114f252d188","abstract_canon_sha256":"d388bb726029bf6ef17866530f8b71190f9e82f5fcd81f3d89f2182be2d9b60c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:11.714030Z","signature_b64":"sgyCGyfKl12Me8XQPfN9e53qwfDS1NkQcP3UXQuu/UDYOLyxvmlGh5yM/cdultKMJsBPXHVsAJ0axTr9tsNXBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b426ea1c43dc6a4924dc5828b03925fbbcbeb12c1b50b79cfbe61d1b3b23d177","last_reissued_at":"2026-05-18T00:39:11.713291Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:11.713291Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.DS","authors_text":"Jieming Mao, Xi Chen, Yuanzhi Li","submitted_at":"2017-07-25T22:03:21Z","abstract_excerpt":"We study the active learning problem of top-$k$ ranking from multi-wise comparisons under the popular multinomial logit model. Our goal is to identify the top-$k$ items with high probability by adaptively querying sets for comparisons and observing the noisy output of the most preferred item from each comparison. To achieve this goal, we design a new active ranking algorithm without using any information about the underlying items' preference scores. We also establish a matching lower bound on the sample complexity even when the set of preference scores is given to the algorithm. These two res"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.08238","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":"1707.08238","created_at":"2026-05-18T00:39:11.713428+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.08238v2","created_at":"2026-05-18T00:39:11.713428+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.08238","created_at":"2026-05-18T00:39:11.713428+00:00"},{"alias_kind":"pith_short_12","alias_value":"WQTOUHCD3RVE","created_at":"2026-05-18T12:31:53.515858+00:00"},{"alias_kind":"pith_short_16","alias_value":"WQTOUHCD3RVESJG4","created_at":"2026-05-18T12:31:53.515858+00:00"},{"alias_kind":"pith_short_8","alias_value":"WQTOUHCD","created_at":"2026-05-18T12:31:53.515858+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2505.16014","citing_title":"Ranking Free RAG: Replacing Re-ranking with Selection in RAG for Sensitive Domains","ref_index":48,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WQTOUHCD3RVESJG4LAULAOJF7O","json":"https://pith.science/pith/WQTOUHCD3RVESJG4LAULAOJF7O.json","graph_json":"https://pith.science/api/pith-number/WQTOUHCD3RVESJG4LAULAOJF7O/graph.json","events_json":"https://pith.science/api/pith-number/WQTOUHCD3RVESJG4LAULAOJF7O/events.json","paper":"https://pith.science/paper/WQTOUHCD"},"agent_actions":{"view_html":"https://pith.science/pith/WQTOUHCD3RVESJG4LAULAOJF7O","download_json":"https://pith.science/pith/WQTOUHCD3RVESJG4LAULAOJF7O.json","view_paper":"https://pith.science/paper/WQTOUHCD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.08238&json=true","fetch_graph":"https://pith.science/api/pith-number/WQTOUHCD3RVESJG4LAULAOJF7O/graph.json","fetch_events":"https://pith.science/api/pith-number/WQTOUHCD3RVESJG4LAULAOJF7O/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WQTOUHCD3RVESJG4LAULAOJF7O/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WQTOUHCD3RVESJG4LAULAOJF7O/action/storage_attestation","attest_author":"https://pith.science/pith/WQTOUHCD3RVESJG4LAULAOJF7O/action/author_attestation","sign_citation":"https://pith.science/pith/WQTOUHCD3RVESJG4LAULAOJF7O/action/citation_signature","submit_replication":"https://pith.science/pith/WQTOUHCD3RVESJG4LAULAOJF7O/action/replication_record"}},"created_at":"2026-05-18T00:39:11.713428+00:00","updated_at":"2026-05-18T00:39:11.713428+00:00"}