{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:XRLXFKQKJRPRCZNYKBI65RHVPM","short_pith_number":"pith:XRLXFKQK","schema_version":"1.0","canonical_sha256":"bc5772aa0a4c5f1165b85051eec4f57b0719897c8c53ca88657e7a70aeb17a23","source":{"kind":"arxiv","id":"1705.07200","version":2},"attestation_state":"computed","paper":{"title":"Smoothed and Average-case Approximation Ratios of Mechanisms: Beyond the Worst-case Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Jie Zhang, Xiaotie Deng, Yansong Gao","submitted_at":"2017-05-19T21:41:53Z","abstract_excerpt":"The approximation ratio has become one of the dominant measures in mechanism design problems. In light of analysis of algorithms, we define the \\emph{smoothed approximation ratio} to compare the performance of the optimal mechanism and a truthful mechanism when the inputs are subject to random perturbations of the worst-case inputs, and define the \\emph{average-case approximation ratio} to compare the performance of these two mechanisms when the inputs follow a distribution. For the one-sided matching problem, \\citet{FFZ:14} show that, amongst all truthful mechanisms, \\emph{random priority} ac"},"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":"1705.07200","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2017-05-19T21:41:53Z","cross_cats_sorted":[],"title_canon_sha256":"a0d191530d2f899db92bbac5146e81f4084af4c5ab0ce55f29b9ace899350555","abstract_canon_sha256":"7fafb06d815ba09098181bf8e8869d74f5b1743495af8d16b89676b6a766ff8b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:41:52.884626Z","signature_b64":"tAh3ZNLctaSj67Lc3kmtInc9MhGleUbpi9mctz1cW/whv8/DpTVDNdzr7sYlIr8Efm9oZlcKLeMNqysKIwcsAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc5772aa0a4c5f1165b85051eec4f57b0719897c8c53ca88657e7a70aeb17a23","last_reissued_at":"2026-05-18T00:41:52.884179Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:41:52.884179Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Smoothed and Average-case Approximation Ratios of Mechanisms: Beyond the Worst-case Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Jie Zhang, Xiaotie Deng, Yansong Gao","submitted_at":"2017-05-19T21:41:53Z","abstract_excerpt":"The approximation ratio has become one of the dominant measures in mechanism design problems. In light of analysis of algorithms, we define the \\emph{smoothed approximation ratio} to compare the performance of the optimal mechanism and a truthful mechanism when the inputs are subject to random perturbations of the worst-case inputs, and define the \\emph{average-case approximation ratio} to compare the performance of these two mechanisms when the inputs follow a distribution. For the one-sided matching problem, \\citet{FFZ:14} show that, amongst all truthful mechanisms, \\emph{random priority} ac"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.07200","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":"1705.07200","created_at":"2026-05-18T00:41:52.884247+00:00"},{"alias_kind":"arxiv_version","alias_value":"1705.07200v2","created_at":"2026-05-18T00:41:52.884247+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.07200","created_at":"2026-05-18T00:41:52.884247+00:00"},{"alias_kind":"pith_short_12","alias_value":"XRLXFKQKJRPR","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_16","alias_value":"XRLXFKQKJRPRCZNY","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_8","alias_value":"XRLXFKQK","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/XRLXFKQKJRPRCZNYKBI65RHVPM","json":"https://pith.science/pith/XRLXFKQKJRPRCZNYKBI65RHVPM.json","graph_json":"https://pith.science/api/pith-number/XRLXFKQKJRPRCZNYKBI65RHVPM/graph.json","events_json":"https://pith.science/api/pith-number/XRLXFKQKJRPRCZNYKBI65RHVPM/events.json","paper":"https://pith.science/paper/XRLXFKQK"},"agent_actions":{"view_html":"https://pith.science/pith/XRLXFKQKJRPRCZNYKBI65RHVPM","download_json":"https://pith.science/pith/XRLXFKQKJRPRCZNYKBI65RHVPM.json","view_paper":"https://pith.science/paper/XRLXFKQK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1705.07200&json=true","fetch_graph":"https://pith.science/api/pith-number/XRLXFKQKJRPRCZNYKBI65RHVPM/graph.json","fetch_events":"https://pith.science/api/pith-number/XRLXFKQKJRPRCZNYKBI65RHVPM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XRLXFKQKJRPRCZNYKBI65RHVPM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XRLXFKQKJRPRCZNYKBI65RHVPM/action/storage_attestation","attest_author":"https://pith.science/pith/XRLXFKQKJRPRCZNYKBI65RHVPM/action/author_attestation","sign_citation":"https://pith.science/pith/XRLXFKQKJRPRCZNYKBI65RHVPM/action/citation_signature","submit_replication":"https://pith.science/pith/XRLXFKQKJRPRCZNYKBI65RHVPM/action/replication_record"}},"created_at":"2026-05-18T00:41:52.884247+00:00","updated_at":"2026-05-18T00:41:52.884247+00:00"}