{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:KMQXLCGXITHBDZUNAD5F77TX6F","short_pith_number":"pith:KMQXLCGX","canonical_record":{"source":{"id":"1707.04916","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2017-07-16T17:12:30Z","cross_cats_sorted":[],"title_canon_sha256":"ba1aceac1ec9dc3b8c168c6396abb0094b6b558adc6cbc6c3e3041bef321d1e3","abstract_canon_sha256":"c6bca24d0e98c9237a1ae461ccf0f12dc7bf1b162b5e6be161489bb05aee2ef0"},"schema_version":"1.0"},"canonical_sha256":"53217588d744ce11e68d00fa5ffe77f1632c5f1102642d5184512d1037543a09","source":{"kind":"arxiv","id":"1707.04916","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.04916","created_at":"2026-05-18T00:40:11Z"},{"alias_kind":"arxiv_version","alias_value":"1707.04916v1","created_at":"2026-05-18T00:40:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.04916","created_at":"2026-05-18T00:40:11Z"},{"alias_kind":"pith_short_12","alias_value":"KMQXLCGXITHB","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_16","alias_value":"KMQXLCGXITHBDZUN","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_8","alias_value":"KMQXLCGX","created_at":"2026-05-18T12:31:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:KMQXLCGXITHBDZUNAD5F77TX6F","target":"record","payload":{"canonical_record":{"source":{"id":"1707.04916","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2017-07-16T17:12:30Z","cross_cats_sorted":[],"title_canon_sha256":"ba1aceac1ec9dc3b8c168c6396abb0094b6b558adc6cbc6c3e3041bef321d1e3","abstract_canon_sha256":"c6bca24d0e98c9237a1ae461ccf0f12dc7bf1b162b5e6be161489bb05aee2ef0"},"schema_version":"1.0"},"canonical_sha256":"53217588d744ce11e68d00fa5ffe77f1632c5f1102642d5184512d1037543a09","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:40:11.795790Z","signature_b64":"hBt9OD17jWpmVkJByjUK78QZFHiNqePlVDOjl7zyDlrlLafxaN5so7CjRDM38XGuNj4IlcGaXr2VaaFV4Bz9AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"53217588d744ce11e68d00fa5ffe77f1632c5f1102642d5184512d1037543a09","last_reissued_at":"2026-05-18T00:40:11.795256Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:40:11.795256Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.04916","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:40:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6roYPlck9EFoax1SOZksHPjs+nb0cjYq8DRoIzMR5VvbRV3WPUC11aukSHq12VJmEGzUmLyQB37b65Tcq3dzDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T23:54:05.302748Z"},"content_sha256":"253dd98d8abd1a7c449d60be96199c5545f54ab6aa0e3e0b498ce0d70da6d6c1","schema_version":"1.0","event_id":"sha256:253dd98d8abd1a7c449d60be96199c5545f54ab6aa0e3e0b498ce0d70da6d6c1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:KMQXLCGXITHBDZUNAD5F77TX6F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-label Music Genre Classification from Audio, Text, and Images Using Deep Features","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Francesco Barbieri, Oriol Nieto, Sergio Oramas, Xavier Serra","submitted_at":"2017-07-16T17:12:30Z","abstract_excerpt":"Music genres allow to categorize musical items that share common characteristics. Although these categories are not mutually exclusive, most related research is traditionally focused on classifying tracks into a single class. Furthermore, these categories (e.g., Pop, Rock) tend to be too broad for certain applications. In this work we aim to expand this task by categorizing musical items into multiple and fine-grained labels, using three different data modalities: audio, text, and images. To this end we present MuMu, a new dataset of more than 31k albums classified into 250 genre classes. For "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.04916","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:40:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4h8CPLuBWr6jYdzoEN68vicM+3MmIf4a61lEmmxq3j4FoeYB5+fLg85DipoVmVbrtyzq+98gYvfBrIkjIznRAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T23:54:05.303357Z"},"content_sha256":"7620c27828414c5a2ae024afda13c9a61195482867158cdbc8dcffc1155b83ff","schema_version":"1.0","event_id":"sha256:7620c27828414c5a2ae024afda13c9a61195482867158cdbc8dcffc1155b83ff"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KMQXLCGXITHBDZUNAD5F77TX6F/bundle.json","state_url":"https://pith.science/pith/KMQXLCGXITHBDZUNAD5F77TX6F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KMQXLCGXITHBDZUNAD5F77TX6F/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":"2026-05-31T23:54:05Z","links":{"resolver":"https://pith.science/pith/KMQXLCGXITHBDZUNAD5F77TX6F","bundle":"https://pith.science/pith/KMQXLCGXITHBDZUNAD5F77TX6F/bundle.json","state":"https://pith.science/pith/KMQXLCGXITHBDZUNAD5F77TX6F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KMQXLCGXITHBDZUNAD5F77TX6F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:KMQXLCGXITHBDZUNAD5F77TX6F","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":"c6bca24d0e98c9237a1ae461ccf0f12dc7bf1b162b5e6be161489bb05aee2ef0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2017-07-16T17:12:30Z","title_canon_sha256":"ba1aceac1ec9dc3b8c168c6396abb0094b6b558adc6cbc6c3e3041bef321d1e3"},"schema_version":"1.0","source":{"id":"1707.04916","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.04916","created_at":"2026-05-18T00:40:11Z"},{"alias_kind":"arxiv_version","alias_value":"1707.04916v1","created_at":"2026-05-18T00:40:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.04916","created_at":"2026-05-18T00:40:11Z"},{"alias_kind":"pith_short_12","alias_value":"KMQXLCGXITHB","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_16","alias_value":"KMQXLCGXITHBDZUN","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_8","alias_value":"KMQXLCGX","created_at":"2026-05-18T12:31:24Z"}],"graph_snapshots":[{"event_id":"sha256:7620c27828414c5a2ae024afda13c9a61195482867158cdbc8dcffc1155b83ff","target":"graph","created_at":"2026-05-18T00:40:11Z","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":"Music genres allow to categorize musical items that share common characteristics. Although these categories are not mutually exclusive, most related research is traditionally focused on classifying tracks into a single class. Furthermore, these categories (e.g., Pop, Rock) tend to be too broad for certain applications. In this work we aim to expand this task by categorizing musical items into multiple and fine-grained labels, using three different data modalities: audio, text, and images. To this end we present MuMu, a new dataset of more than 31k albums classified into 250 genre classes. For ","authors_text":"Francesco Barbieri, Oriol Nieto, Sergio Oramas, Xavier Serra","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2017-07-16T17:12:30Z","title":"Multi-label Music Genre Classification from Audio, Text, and Images Using Deep Features"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.04916","kind":"arxiv","version":1},"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":"sha256:253dd98d8abd1a7c449d60be96199c5545f54ab6aa0e3e0b498ce0d70da6d6c1","target":"record","created_at":"2026-05-18T00:40:11Z","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":"c6bca24d0e98c9237a1ae461ccf0f12dc7bf1b162b5e6be161489bb05aee2ef0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2017-07-16T17:12:30Z","title_canon_sha256":"ba1aceac1ec9dc3b8c168c6396abb0094b6b558adc6cbc6c3e3041bef321d1e3"},"schema_version":"1.0","source":{"id":"1707.04916","kind":"arxiv","version":1}},"canonical_sha256":"53217588d744ce11e68d00fa5ffe77f1632c5f1102642d5184512d1037543a09","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"53217588d744ce11e68d00fa5ffe77f1632c5f1102642d5184512d1037543a09","first_computed_at":"2026-05-18T00:40:11.795256Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:40:11.795256Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hBt9OD17jWpmVkJByjUK78QZFHiNqePlVDOjl7zyDlrlLafxaN5so7CjRDM38XGuNj4IlcGaXr2VaaFV4Bz9AA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:40:11.795790Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.04916","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:253dd98d8abd1a7c449d60be96199c5545f54ab6aa0e3e0b498ce0d70da6d6c1","sha256:7620c27828414c5a2ae024afda13c9a61195482867158cdbc8dcffc1155b83ff"],"state_sha256":"587fe2be1ef2b65295d8cff4cb21568144ecea75e4c6d261e7d407f97acf2b55"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i1PIwTIIuWRos27FLMZnxsMS6LnEbS2Xf6bZigkAHk/7WpWBgrPEpcuh6L6MmsBAyCx+OUd7EUku8K0Wh2q5Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T23:54:05.306610Z","bundle_sha256":"029b69c94e788304deb0e33d0df099dca22941e03e823d728b788d26b019379c"}}