{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:POJTNOYTBSRL4QKUJLWPRI6N7N","short_pith_number":"pith:POJTNOYT","schema_version":"1.0","canonical_sha256":"7b9336bb130ca2be41544aecf8a3cdfb6c07a814725a7a3f2c403de23db588ef","source":{"kind":"arxiv","id":"2509.00132","version":1},"attestation_state":"computed","paper":{"title":"CoComposer: LLM Multi-agent Collaborative Music Composition","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.MM","eess.AS"],"primary_cat":"cs.SD","authors_text":"Aske Plaat, Niki van Stein, Peiwen Xing","submitted_at":"2025-08-29T14:15:12Z","abstract_excerpt":"Existing AI Music composition tools are limited in generation duration, musical quality, and controllability. We introduce CoComposer, a multi-agent system that consists of five collaborating agents, each with a task based on the traditional music composition workflow. Using the AudioBox-Aesthetics system, we experimentally evaluate CoComposer on four compositional criteria. We test with three LLMs (GPT-4o, DeepSeek-V3-0324, Gemini-2.5-Flash), and find (1) that CoComposer outperforms existing multi-agent LLM-based systems in music quality, and (2) compared to a single-agent system, in producti"},"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":"2509.00132","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2025-08-29T14:15:12Z","cross_cats_sorted":["cs.AI","cs.MM","eess.AS"],"title_canon_sha256":"c336b9ee66c80c0c51b384f47f24107a8ae0a7825247063f7da00c03f0c34282","abstract_canon_sha256":"9a507cedad5cb5a409a573625916b3140e9dfd357011167c7751310c986bb12a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:02:09.938313Z","signature_b64":"DqCFAzzs/TfbyzYJ12H4p9F7cU1Zz1beb8yFiiZYhcuJ+oqBE9C9f4NXetbklMTR5rlYSZS0aIhZggOUx3UNCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7b9336bb130ca2be41544aecf8a3cdfb6c07a814725a7a3f2c403de23db588ef","last_reissued_at":"2026-07-05T12:02:09.937826Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:02:09.937826Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CoComposer: LLM Multi-agent Collaborative Music Composition","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.MM","eess.AS"],"primary_cat":"cs.SD","authors_text":"Aske Plaat, Niki van Stein, Peiwen Xing","submitted_at":"2025-08-29T14:15:12Z","abstract_excerpt":"Existing AI Music composition tools are limited in generation duration, musical quality, and controllability. We introduce CoComposer, a multi-agent system that consists of five collaborating agents, each with a task based on the traditional music composition workflow. Using the AudioBox-Aesthetics system, we experimentally evaluate CoComposer on four compositional criteria. We test with three LLMs (GPT-4o, DeepSeek-V3-0324, Gemini-2.5-Flash), and find (1) that CoComposer outperforms existing multi-agent LLM-based systems in music quality, and (2) compared to a single-agent system, in producti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.00132","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2509.00132/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2509.00132","created_at":"2026-07-05T12:02:09.937883+00:00"},{"alias_kind":"arxiv_version","alias_value":"2509.00132v1","created_at":"2026-07-05T12:02:09.937883+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.00132","created_at":"2026-07-05T12:02:09.937883+00:00"},{"alias_kind":"pith_short_12","alias_value":"POJTNOYTBSRL","created_at":"2026-07-05T12:02:09.937883+00:00"},{"alias_kind":"pith_short_16","alias_value":"POJTNOYTBSRL4QKU","created_at":"2026-07-05T12:02:09.937883+00:00"},{"alias_kind":"pith_short_8","alias_value":"POJTNOYT","created_at":"2026-07-05T12:02:09.937883+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.22708","citing_title":"Libretto: Giving LLM Agents a Sense of Musical Structure","ref_index":17,"is_internal_anchor":false},{"citing_arxiv_id":"2605.13431","citing_title":"Text2Score: Generating Sheet Music From Textual Prompts","ref_index":26,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/POJTNOYTBSRL4QKUJLWPRI6N7N","json":"https://pith.science/pith/POJTNOYTBSRL4QKUJLWPRI6N7N.json","graph_json":"https://pith.science/api/pith-number/POJTNOYTBSRL4QKUJLWPRI6N7N/graph.json","events_json":"https://pith.science/api/pith-number/POJTNOYTBSRL4QKUJLWPRI6N7N/events.json","paper":"https://pith.science/paper/POJTNOYT"},"agent_actions":{"view_html":"https://pith.science/pith/POJTNOYTBSRL4QKUJLWPRI6N7N","download_json":"https://pith.science/pith/POJTNOYTBSRL4QKUJLWPRI6N7N.json","view_paper":"https://pith.science/paper/POJTNOYT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2509.00132&json=true","fetch_graph":"https://pith.science/api/pith-number/POJTNOYTBSRL4QKUJLWPRI6N7N/graph.json","fetch_events":"https://pith.science/api/pith-number/POJTNOYTBSRL4QKUJLWPRI6N7N/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/POJTNOYTBSRL4QKUJLWPRI6N7N/action/timestamp_anchor","attest_storage":"https://pith.science/pith/POJTNOYTBSRL4QKUJLWPRI6N7N/action/storage_attestation","attest_author":"https://pith.science/pith/POJTNOYTBSRL4QKUJLWPRI6N7N/action/author_attestation","sign_citation":"https://pith.science/pith/POJTNOYTBSRL4QKUJLWPRI6N7N/action/citation_signature","submit_replication":"https://pith.science/pith/POJTNOYTBSRL4QKUJLWPRI6N7N/action/replication_record"}},"created_at":"2026-07-05T12:02:09.937883+00:00","updated_at":"2026-07-05T12:02:09.937883+00:00"}