{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:PQMHPHPNT7LB6BMLEKKR7HM44V","short_pith_number":"pith:PQMHPHPN","canonical_record":{"source":{"id":"1710.11418","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-10-31T11:57:00Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"17564adf40ca366bdff2296aed89675a3d9cedde1c53fd51e010c511d01255f9","abstract_canon_sha256":"0a14b11bd025d1767ccf7bf395d47ce197527ad67ce11dfc97b61ff39e1c8214"},"schema_version":"1.0"},"canonical_sha256":"7c18779ded9fd61f058b22951f9d9ce5423b87048e65040c1c4b0f0ddcb0b4d9","source":{"kind":"arxiv","id":"1710.11418","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.11418","created_at":"2026-05-18T00:11:57Z"},{"alias_kind":"arxiv_version","alias_value":"1710.11418v2","created_at":"2026-05-18T00:11:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.11418","created_at":"2026-05-18T00:11:57Z"},{"alias_kind":"pith_short_12","alias_value":"PQMHPHPNT7LB","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_16","alias_value":"PQMHPHPNT7LB6BML","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_8","alias_value":"PQMHPHPN","created_at":"2026-05-18T12:31:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:PQMHPHPNT7LB6BMLEKKR7HM44V","target":"record","payload":{"canonical_record":{"source":{"id":"1710.11418","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-10-31T11:57:00Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"17564adf40ca366bdff2296aed89675a3d9cedde1c53fd51e010c511d01255f9","abstract_canon_sha256":"0a14b11bd025d1767ccf7bf395d47ce197527ad67ce11dfc97b61ff39e1c8214"},"schema_version":"1.0"},"canonical_sha256":"7c18779ded9fd61f058b22951f9d9ce5423b87048e65040c1c4b0f0ddcb0b4d9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:11:57.795950Z","signature_b64":"g0EaUN16Fg18oNIMVGsJBxFhbYoh24SDBn5k+KDmZBaRV4kPUQiBRfrZ7EEw3/FaUfJRQI36DcMFgoKfX8dOAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7c18779ded9fd61f058b22951f9d9ce5423b87048e65040c1c4b0f0ddcb0b4d9","last_reissued_at":"2026-05-18T00:11:57.795434Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:11:57.795434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1710.11418","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:11:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OR16DJK50Wetzz9HGk/3ZR1tVEeYVrRVj2QaRf0fjbG7quUF4BOdNih9C/dK+m6QO3OEJV2YnyilW76aeVzOAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T06:50:00.933382Z"},"content_sha256":"ee0f8e060e06e068339612743444f34a8f57594a27bdbc37fa7c00bf9c6de843","schema_version":"1.0","event_id":"sha256:ee0f8e060e06e068339612743444f34a8f57594a27bdbc37fa7c00bf9c6de843"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:PQMHPHPNT7LB6BMLEKKR7HM44V","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Polyphonic Music Generation with Sequence Generative Adversarial Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.SD","authors_text":"Sang-gil Lee, Seonwoo Min, Sungroh Yoon, Uiwon Hwang","submitted_at":"2017-10-31T11:57:00Z","abstract_excerpt":"We propose an application of sequence generative adversarial networks (SeqGAN), which are generative adversarial networks for discrete sequence generation, for creating polyphonic musical sequences. Instead of a monophonic melody generation suggested in the original work, we present an efficient representation of a polyphony MIDI file that simultaneously captures chords and melodies with dynamic timings. The proposed method condenses duration, octaves, and keys of both melodies and chords into a single word vector representation, and recurrent neural networks learn to predict distributions of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.11418","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:11:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CqDfFf2JdWIlUuW+KAnkIvjKWj6T+MxBQWSIeD+va8Z1nSmw+v1u3q1Y2mclEs33qd4ZX4Wn+IEzi7KjKiVWDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T06:50:00.934133Z"},"content_sha256":"387b7d2c105bff095d10c82c86bca7ef5aafe81f3e69df926cb8ac9c8c68a958","schema_version":"1.0","event_id":"sha256:387b7d2c105bff095d10c82c86bca7ef5aafe81f3e69df926cb8ac9c8c68a958"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PQMHPHPNT7LB6BMLEKKR7HM44V/bundle.json","state_url":"https://pith.science/pith/PQMHPHPNT7LB6BMLEKKR7HM44V/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PQMHPHPNT7LB6BMLEKKR7HM44V/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-10T06:50:00Z","links":{"resolver":"https://pith.science/pith/PQMHPHPNT7LB6BMLEKKR7HM44V","bundle":"https://pith.science/pith/PQMHPHPNT7LB6BMLEKKR7HM44V/bundle.json","state":"https://pith.science/pith/PQMHPHPNT7LB6BMLEKKR7HM44V/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PQMHPHPNT7LB6BMLEKKR7HM44V/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:PQMHPHPNT7LB6BMLEKKR7HM44V","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"0a14b11bd025d1767ccf7bf395d47ce197527ad67ce11dfc97b61ff39e1c8214","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-10-31T11:57:00Z","title_canon_sha256":"17564adf40ca366bdff2296aed89675a3d9cedde1c53fd51e010c511d01255f9"},"schema_version":"1.0","source":{"id":"1710.11418","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.11418","created_at":"2026-05-18T00:11:57Z"},{"alias_kind":"arxiv_version","alias_value":"1710.11418v2","created_at":"2026-05-18T00:11:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.11418","created_at":"2026-05-18T00:11:57Z"},{"alias_kind":"pith_short_12","alias_value":"PQMHPHPNT7LB","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_16","alias_value":"PQMHPHPNT7LB6BML","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_8","alias_value":"PQMHPHPN","created_at":"2026-05-18T12:31:37Z"}],"graph_snapshots":[{"event_id":"sha256:387b7d2c105bff095d10c82c86bca7ef5aafe81f3e69df926cb8ac9c8c68a958","target":"graph","created_at":"2026-05-18T00:11:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"We propose an application of sequence generative adversarial networks (SeqGAN), which are generative adversarial networks for discrete sequence generation, for creating polyphonic musical sequences. Instead of a monophonic melody generation suggested in the original work, we present an efficient representation of a polyphony MIDI file that simultaneously captures chords and melodies with dynamic timings. The proposed method condenses duration, octaves, and keys of both melodies and chords into a single word vector representation, and recurrent neural networks learn to predict distributions of ","authors_text":"Sang-gil Lee, Seonwoo Min, Sungroh Yoon, Uiwon Hwang","cross_cats":["eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-10-31T11:57:00Z","title":"Polyphonic Music Generation with Sequence Generative Adversarial Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.11418","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:ee0f8e060e06e068339612743444f34a8f57594a27bdbc37fa7c00bf9c6de843","target":"record","created_at":"2026-05-18T00:11:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"0a14b11bd025d1767ccf7bf395d47ce197527ad67ce11dfc97b61ff39e1c8214","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2017-10-31T11:57:00Z","title_canon_sha256":"17564adf40ca366bdff2296aed89675a3d9cedde1c53fd51e010c511d01255f9"},"schema_version":"1.0","source":{"id":"1710.11418","kind":"arxiv","version":2}},"canonical_sha256":"7c18779ded9fd61f058b22951f9d9ce5423b87048e65040c1c4b0f0ddcb0b4d9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7c18779ded9fd61f058b22951f9d9ce5423b87048e65040c1c4b0f0ddcb0b4d9","first_computed_at":"2026-05-18T00:11:57.795434Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:11:57.795434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"g0EaUN16Fg18oNIMVGsJBxFhbYoh24SDBn5k+KDmZBaRV4kPUQiBRfrZ7EEw3/FaUfJRQI36DcMFgoKfX8dOAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:11:57.795950Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.11418","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ee0f8e060e06e068339612743444f34a8f57594a27bdbc37fa7c00bf9c6de843","sha256:387b7d2c105bff095d10c82c86bca7ef5aafe81f3e69df926cb8ac9c8c68a958"],"state_sha256":"8ea105f451339e9690632e8abd74c96183e941a7e7edf1c1b47bd0fe8c2a1b99"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+eqW1qsWg5AZ0+JYrAAJAaab257GZwjVlJkKhhHC6s4hFNW7YbCj2YXUCV4qNVOo76DZaK2oYpc4TY2pjCizCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T06:50:00.938336Z","bundle_sha256":"b7ae135629150a7fb7758ec0705dad7ac61f592f8899bdd4b03f5b0cb7d93c03"}}