{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:RYHTZUPSUUSKLZ2UKS5WTYA6Y7","short_pith_number":"pith:RYHTZUPS","schema_version":"1.0","canonical_sha256":"8e0f3cd1f2a524a5e75454bb69e01ec7da296bc2ec2250f53f8da95442afc032","source":{"kind":"arxiv","id":"1606.05829","version":1},"attestation_state":"computed","paper":{"title":"Can Machine Generate Traditional Chinese Poetry? A Feigenbaum Test","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dong Wang, Qixin Wang, Tianyi Luo","submitted_at":"2016-06-19T03:17:29Z","abstract_excerpt":"Recent progress in neural learning demonstrated that machines can do well in regularized tasks, e.g., the game of Go. However, artistic activities such as poem generation are still widely regarded as human's special capability. In this paper, we demonstrate that a simple neural model can imitate human in some tasks of art generation. We particularly focus on traditional Chinese poetry, and show that machines can do as well as many contemporary poets and weakly pass the Feigenbaum Test, a variant of Turing test in professional domains. Our method is based on an attention-based recurrent neural "},"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":"1606.05829","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-19T03:17:29Z","cross_cats_sorted":[],"title_canon_sha256":"60d861e909e8eafc3401f98340fa6bfb2bc7fa5d322900afbc9a5a29f6299d19","abstract_canon_sha256":"fe73793c8dd1f4c34a22c58d6588b493bc708c4702cc892fcefeb07f787c83ec"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:12:15.968244Z","signature_b64":"thHvkmisMHWUrP7cIAIvkj48B7wPqycfPgpFFpdprksrhQgATFuaIhxEQ+bfUMWL86IEe1igQIyn3r7wStCDDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8e0f3cd1f2a524a5e75454bb69e01ec7da296bc2ec2250f53f8da95442afc032","last_reissued_at":"2026-05-18T01:12:15.967877Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:12:15.967877Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Can Machine Generate Traditional Chinese Poetry? A Feigenbaum Test","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dong Wang, Qixin Wang, Tianyi Luo","submitted_at":"2016-06-19T03:17:29Z","abstract_excerpt":"Recent progress in neural learning demonstrated that machines can do well in regularized tasks, e.g., the game of Go. However, artistic activities such as poem generation are still widely regarded as human's special capability. In this paper, we demonstrate that a simple neural model can imitate human in some tasks of art generation. We particularly focus on traditional Chinese poetry, and show that machines can do as well as many contemporary poets and weakly pass the Feigenbaum Test, a variant of Turing test in professional domains. Our method is based on an attention-based recurrent neural "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.05829","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":""},"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":"1606.05829","created_at":"2026-05-18T01:12:15.967950+00:00"},{"alias_kind":"arxiv_version","alias_value":"1606.05829v1","created_at":"2026-05-18T01:12:15.967950+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.05829","created_at":"2026-05-18T01:12:15.967950+00:00"},{"alias_kind":"pith_short_12","alias_value":"RYHTZUPSUUSK","created_at":"2026-05-18T12:30:41.710351+00:00"},{"alias_kind":"pith_short_16","alias_value":"RYHTZUPSUUSKLZ2U","created_at":"2026-05-18T12:30:41.710351+00:00"},{"alias_kind":"pith_short_8","alias_value":"RYHTZUPS","created_at":"2026-05-18T12:30:41.710351+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/RYHTZUPSUUSKLZ2UKS5WTYA6Y7","json":"https://pith.science/pith/RYHTZUPSUUSKLZ2UKS5WTYA6Y7.json","graph_json":"https://pith.science/api/pith-number/RYHTZUPSUUSKLZ2UKS5WTYA6Y7/graph.json","events_json":"https://pith.science/api/pith-number/RYHTZUPSUUSKLZ2UKS5WTYA6Y7/events.json","paper":"https://pith.science/paper/RYHTZUPS"},"agent_actions":{"view_html":"https://pith.science/pith/RYHTZUPSUUSKLZ2UKS5WTYA6Y7","download_json":"https://pith.science/pith/RYHTZUPSUUSKLZ2UKS5WTYA6Y7.json","view_paper":"https://pith.science/paper/RYHTZUPS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1606.05829&json=true","fetch_graph":"https://pith.science/api/pith-number/RYHTZUPSUUSKLZ2UKS5WTYA6Y7/graph.json","fetch_events":"https://pith.science/api/pith-number/RYHTZUPSUUSKLZ2UKS5WTYA6Y7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RYHTZUPSUUSKLZ2UKS5WTYA6Y7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RYHTZUPSUUSKLZ2UKS5WTYA6Y7/action/storage_attestation","attest_author":"https://pith.science/pith/RYHTZUPSUUSKLZ2UKS5WTYA6Y7/action/author_attestation","sign_citation":"https://pith.science/pith/RYHTZUPSUUSKLZ2UKS5WTYA6Y7/action/citation_signature","submit_replication":"https://pith.science/pith/RYHTZUPSUUSKLZ2UKS5WTYA6Y7/action/replication_record"}},"created_at":"2026-05-18T01:12:15.967950+00:00","updated_at":"2026-05-18T01:12:15.967950+00:00"}