{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:UE7MAAK65EDRP7YTUK466URJ42","short_pith_number":"pith:UE7MAAK6","schema_version":"1.0","canonical_sha256":"a13ec0015ee90717ff13a2b9ef5229e699b3effd66a7829bfb52024d9b94dbc2","source":{"kind":"arxiv","id":"2412.19303","version":1},"attestation_state":"computed","paper":{"title":"Manga Generation via Layout-controllable Diffusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dengjie Li, Lingfeng Tan, Siyu Chen, Yao Zhou, Yujie Zhong, Zenghao Bao, Zheng Zhao","submitted_at":"2024-12-26T17:52:19Z","abstract_excerpt":"Generating comics through text is widely studied. However, there are few studies on generating multi-panel Manga (Japanese comics) solely based on plain text. Japanese manga contains multiple panels on a single page, with characteristics such as coherence in storytelling, reasonable and diverse page layouts, consistency in characters, and semantic correspondence between panel drawings and panel scripts. Therefore, generating manga poses a significant challenge. This paper presents the manga generation task and constructs the Manga109Story dataset for studying manga generation solely from plain"},"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":"2412.19303","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-26T17:52:19Z","cross_cats_sorted":[],"title_canon_sha256":"67687f849d50b8bfeb5791176a0340f3244939d7b7bdc76e6a46f3e0972af2f2","abstract_canon_sha256":"d67cd766e19f87e5b03cb379bc0f73231fafbb6a82c490181f280ad8d6fac63c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:54:33.687307Z","signature_b64":"/XxHk5vfHCmevthBUvfY0jmBMLBmuxoC2nUiHeMBUkI88ieQtC8T8bKGpJzhtw1t6j8BEV/VNGKINTNsiV+QAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a13ec0015ee90717ff13a2b9ef5229e699b3effd66a7829bfb52024d9b94dbc2","last_reissued_at":"2026-07-05T09:54:33.686836Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:54:33.686836Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Manga Generation via Layout-controllable Diffusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dengjie Li, Lingfeng Tan, Siyu Chen, Yao Zhou, Yujie Zhong, Zenghao Bao, Zheng Zhao","submitted_at":"2024-12-26T17:52:19Z","abstract_excerpt":"Generating comics through text is widely studied. However, there are few studies on generating multi-panel Manga (Japanese comics) solely based on plain text. Japanese manga contains multiple panels on a single page, with characteristics such as coherence in storytelling, reasonable and diverse page layouts, consistency in characters, and semantic correspondence between panel drawings and panel scripts. Therefore, generating manga poses a significant challenge. This paper presents the manga generation task and constructs the Manga109Story dataset for studying manga generation solely from plain"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.19303","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/2412.19303/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":"2412.19303","created_at":"2026-07-05T09:54:33.686894+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.19303v1","created_at":"2026-07-05T09:54:33.686894+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.19303","created_at":"2026-07-05T09:54:33.686894+00:00"},{"alias_kind":"pith_short_12","alias_value":"UE7MAAK65EDR","created_at":"2026-07-05T09:54:33.686894+00:00"},{"alias_kind":"pith_short_16","alias_value":"UE7MAAK65EDRP7YT","created_at":"2026-07-05T09:54:33.686894+00:00"},{"alias_kind":"pith_short_8","alias_value":"UE7MAAK6","created_at":"2026-07-05T09:54:33.686894+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2509.04123","citing_title":"TaleDiffusion: Multi-Character Story Generation with Dialogue Rendering","ref_index":11,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/UE7MAAK65EDRP7YTUK466URJ42","json":"https://pith.science/pith/UE7MAAK65EDRP7YTUK466URJ42.json","graph_json":"https://pith.science/api/pith-number/UE7MAAK65EDRP7YTUK466URJ42/graph.json","events_json":"https://pith.science/api/pith-number/UE7MAAK65EDRP7YTUK466URJ42/events.json","paper":"https://pith.science/paper/UE7MAAK6"},"agent_actions":{"view_html":"https://pith.science/pith/UE7MAAK65EDRP7YTUK466URJ42","download_json":"https://pith.science/pith/UE7MAAK65EDRP7YTUK466URJ42.json","view_paper":"https://pith.science/paper/UE7MAAK6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.19303&json=true","fetch_graph":"https://pith.science/api/pith-number/UE7MAAK65EDRP7YTUK466URJ42/graph.json","fetch_events":"https://pith.science/api/pith-number/UE7MAAK65EDRP7YTUK466URJ42/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UE7MAAK65EDRP7YTUK466URJ42/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UE7MAAK65EDRP7YTUK466URJ42/action/storage_attestation","attest_author":"https://pith.science/pith/UE7MAAK65EDRP7YTUK466URJ42/action/author_attestation","sign_citation":"https://pith.science/pith/UE7MAAK65EDRP7YTUK466URJ42/action/citation_signature","submit_replication":"https://pith.science/pith/UE7MAAK65EDRP7YTUK466URJ42/action/replication_record"}},"created_at":"2026-07-05T09:54:33.686894+00:00","updated_at":"2026-07-05T09:54:33.686894+00:00"}