{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:JTUKI6DZ34DYQRYWYICCDNEJ6E","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":"3d0bd6b89fbc1a6f1fd0c842b5b604bf3fe78898a2d96c51b4bd2a1bf5d0978b","cross_cats_sorted":["cs.AI","cs.LG","eess.AS"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.SD","submitted_at":"2023-05-25T05:02:35Z","title_canon_sha256":"4ccdeb3db1172da8579273f00eaccbced672668e5e5ed4dcf743ce2660c79727"},"schema_version":"1.0","source":{"id":"2305.15719","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.15719","created_at":"2026-07-05T06:13:43Z"},{"alias_kind":"arxiv_version","alias_value":"2305.15719v1","created_at":"2026-07-05T06:13:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.15719","created_at":"2026-07-05T06:13:43Z"},{"alias_kind":"pith_short_12","alias_value":"JTUKI6DZ34DY","created_at":"2026-07-05T06:13:43Z"},{"alias_kind":"pith_short_16","alias_value":"JTUKI6DZ34DYQRYW","created_at":"2026-07-05T06:13:43Z"},{"alias_kind":"pith_short_8","alias_value":"JTUKI6DZ","created_at":"2026-07-05T06:13:43Z"}],"graph_snapshots":[{"event_id":"sha256:b556421520d336a0348b52fc0749cf8161dc0617d984462e2bf6c3e967aaed12","target":"graph","created_at":"2026-07-05T06:13:43Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2305.15719/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent progress in music generation has been remarkably advanced by the state-of-the-art MusicLM, which comprises a hierarchy of three LMs, respectively, for semantic, coarse acoustic, and fine acoustic modelings. Yet, sampling with the MusicLM requires processing through these LMs one by one to obtain the fine-grained acoustic tokens, making it computationally expensive and prohibitive for a real-time generation. Efficient music generation with a quality on par with MusicLM remains a significant challenge. In this paper, we present MeLoDy (M for music; L for LM; D for diffusion), an LM-guided","authors_text":"Jitong Chen, Max W. Y. Lam, Mingbo Ma, Ming Tu, Qiao Tian, Rui Xia, Siyuan Feng, Tang Li, Xuchen Song, Yuliang Ji, Yuping Wang, Yuxuan Wang, Zongyu Yin","cross_cats":["cs.AI","cs.LG","eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.SD","submitted_at":"2023-05-25T05:02:35Z","title":"Efficient Neural Music Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.15719","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":"sha256:479109f9385bddcd550895f767acd2a58af4e991aeceacb9775ec3cf435aea67","target":"record","created_at":"2026-07-05T06:13:43Z","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":"3d0bd6b89fbc1a6f1fd0c842b5b604bf3fe78898a2d96c51b4bd2a1bf5d0978b","cross_cats_sorted":["cs.AI","cs.LG","eess.AS"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.SD","submitted_at":"2023-05-25T05:02:35Z","title_canon_sha256":"4ccdeb3db1172da8579273f00eaccbced672668e5e5ed4dcf743ce2660c79727"},"schema_version":"1.0","source":{"id":"2305.15719","kind":"arxiv","version":1}},"canonical_sha256":"4ce8a47879df07884716c20421b489f13774cc9a6d178af9fe2c48d969fac53d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4ce8a47879df07884716c20421b489f13774cc9a6d178af9fe2c48d969fac53d","first_computed_at":"2026-07-05T06:13:43.828256Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:13:43.828256Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"q36JiOBSDFznWy9PIPc8yaaSPpqrgK2fl5OwRHzMYTNlU4IkDJVWsy7/mdouPhZPAeTmFXLNuurUDfoEFgZyBA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:13:43.828670Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.15719","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:479109f9385bddcd550895f767acd2a58af4e991aeceacb9775ec3cf435aea67","sha256:b556421520d336a0348b52fc0749cf8161dc0617d984462e2bf6c3e967aaed12"],"state_sha256":"82525d7295e88fc155243c0e90c139de6087a3c8e11dc0eefd0422d1b41d73c7"}