{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:TGSDT2LTT27AXC34O536L2BWYD","short_pith_number":"pith:TGSDT2LT","schema_version":"1.0","canonical_sha256":"99a439e9739ebe0b8b7c7777e5e836c0c06f09d35e5e3dd397409d9f77d6e26f","source":{"kind":"arxiv","id":"2311.13687","version":1},"attestation_state":"computed","paper":{"title":"Beat-Aligned Spectrogram-to-Sequence Generation of Rhythm-Game Charts","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.MM","cs.SD","eess.AS"],"primary_cat":"cs.LG","authors_text":"Jayeon Yi, Kyogu Lee, Sungho Lee","submitted_at":"2023-11-22T20:47:52Z","abstract_excerpt":"In the heart of \"rhythm games\" - games where players must perform actions in sync with a piece of music - are \"charts\", the directives to be given to players. We newly formulate chart generation as a sequence generation task and train a Transformer using a large dataset. We also introduce tempo-informed preprocessing and training procedures, some of which are suggested to be integral for a successful training. Our model is found to outperform the baselines on a large dataset, and is also found to benefit from pretraining and finetuning."},"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":"2311.13687","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-22T20:47:52Z","cross_cats_sorted":["cs.MM","cs.SD","eess.AS"],"title_canon_sha256":"fa70d3efe57f16f7a6a9644cafa244bf84e2125305bb62c36a30fd1697351297","abstract_canon_sha256":"8d0aeab2d9a3e94f26fa0c447ffc993917225e7bcd3bc4583a15c9bc9920c137"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:16:06.244637Z","signature_b64":"/Ti0vHmE40EmdI7Eo9GlL01eYXmIlVBMB02pjKIquTxgSAU7TS23xmU5RXfPkTMGgjDtaRojdahmQIyLGz7xBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"99a439e9739ebe0b8b7c7777e5e836c0c06f09d35e5e3dd397409d9f77d6e26f","last_reissued_at":"2026-07-05T07:16:06.244194Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:16:06.244194Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Beat-Aligned Spectrogram-to-Sequence Generation of Rhythm-Game Charts","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.MM","cs.SD","eess.AS"],"primary_cat":"cs.LG","authors_text":"Jayeon Yi, Kyogu Lee, Sungho Lee","submitted_at":"2023-11-22T20:47:52Z","abstract_excerpt":"In the heart of \"rhythm games\" - games where players must perform actions in sync with a piece of music - are \"charts\", the directives to be given to players. We newly formulate chart generation as a sequence generation task and train a Transformer using a large dataset. We also introduce tempo-informed preprocessing and training procedures, some of which are suggested to be integral for a successful training. Our model is found to outperform the baselines on a large dataset, and is also found to benefit from pretraining and finetuning."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.13687","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/2311.13687/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":"2311.13687","created_at":"2026-07-05T07:16:06.244267+00:00"},{"alias_kind":"arxiv_version","alias_value":"2311.13687v1","created_at":"2026-07-05T07:16:06.244267+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.13687","created_at":"2026-07-05T07:16:06.244267+00:00"},{"alias_kind":"pith_short_12","alias_value":"TGSDT2LTT27A","created_at":"2026-07-05T07:16:06.244267+00:00"},{"alias_kind":"pith_short_16","alias_value":"TGSDT2LTT27AXC34","created_at":"2026-07-05T07:16:06.244267+00:00"},{"alias_kind":"pith_short_8","alias_value":"TGSDT2LT","created_at":"2026-07-05T07:16:06.244267+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/TGSDT2LTT27AXC34O536L2BWYD","json":"https://pith.science/pith/TGSDT2LTT27AXC34O536L2BWYD.json","graph_json":"https://pith.science/api/pith-number/TGSDT2LTT27AXC34O536L2BWYD/graph.json","events_json":"https://pith.science/api/pith-number/TGSDT2LTT27AXC34O536L2BWYD/events.json","paper":"https://pith.science/paper/TGSDT2LT"},"agent_actions":{"view_html":"https://pith.science/pith/TGSDT2LTT27AXC34O536L2BWYD","download_json":"https://pith.science/pith/TGSDT2LTT27AXC34O536L2BWYD.json","view_paper":"https://pith.science/paper/TGSDT2LT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2311.13687&json=true","fetch_graph":"https://pith.science/api/pith-number/TGSDT2LTT27AXC34O536L2BWYD/graph.json","fetch_events":"https://pith.science/api/pith-number/TGSDT2LTT27AXC34O536L2BWYD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TGSDT2LTT27AXC34O536L2BWYD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TGSDT2LTT27AXC34O536L2BWYD/action/storage_attestation","attest_author":"https://pith.science/pith/TGSDT2LTT27AXC34O536L2BWYD/action/author_attestation","sign_citation":"https://pith.science/pith/TGSDT2LTT27AXC34O536L2BWYD/action/citation_signature","submit_replication":"https://pith.science/pith/TGSDT2LTT27AXC34O536L2BWYD/action/replication_record"}},"created_at":"2026-07-05T07:16:06.244267+00:00","updated_at":"2026-07-05T07:16:06.244267+00:00"}