{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4NSB36X4MWKGQXHTELYEQV23DZ","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":"4f28063ff2b617e997f85cbff1e5551a76138e125f3f5cee44fd1afd8b135359","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-05T14:38:07Z","title_canon_sha256":"57c2afd5314f1145dbea977a9db0a6f811570bc917b7806d7e59d2d36c69d821"},"schema_version":"1.0","source":{"id":"2509.05146","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.05146","created_at":"2026-07-05T12:05:36Z"},{"alias_kind":"arxiv_version","alias_value":"2509.05146v1","created_at":"2026-07-05T12:05:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.05146","created_at":"2026-07-05T12:05:36Z"},{"alias_kind":"pith_short_12","alias_value":"4NSB36X4MWKG","created_at":"2026-07-05T12:05:36Z"},{"alias_kind":"pith_short_16","alias_value":"4NSB36X4MWKGQXHT","created_at":"2026-07-05T12:05:36Z"},{"alias_kind":"pith_short_8","alias_value":"4NSB36X4","created_at":"2026-07-05T12:05:36Z"}],"graph_snapshots":[{"event_id":"sha256:a49c4101c7c92205b416437c9a29a3804ad956c07654f5f17a398c5e03f37a76","target":"graph","created_at":"2026-07-05T12:05:36Z","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/2509.05146/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In-Image Machine Translation (IIMT) aims to translate images containing texts from one language to another. Current research of end-to-end IIMT mainly conducts on synthetic data, with simple background, single font, fixed text position, and bilingual translation, which can not fully reflect real world, causing a significant gap between the research and practical conditions. To facilitate research of IIMT in real-world scenarios, we explore Practical In-Image Multilingual Machine Translation (IIMMT). In order to convince the lack of publicly available data, we annotate the PRIM dataset, which c","authors_text":"Chong Feng, Heyan Huang, Xin Li, Yanzhi Tian, Yuhang Guo, Zeming Liu, Zhengyang Liu","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-05T14:38:07Z","title":"PRIM: Towards Practical In-Image Multilingual Machine Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.05146","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:a570abb0fca41cefe6f053ed2d202c38206bb9c32c27da91a06949efab93948c","target":"record","created_at":"2026-07-05T12:05:36Z","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":"4f28063ff2b617e997f85cbff1e5551a76138e125f3f5cee44fd1afd8b135359","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-05T14:38:07Z","title_canon_sha256":"57c2afd5314f1145dbea977a9db0a6f811570bc917b7806d7e59d2d36c69d821"},"schema_version":"1.0","source":{"id":"2509.05146","kind":"arxiv","version":1}},"canonical_sha256":"e3641dfafc6594685cf322f048575b1e742c0710be375f9c947cafcae5b316a8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e3641dfafc6594685cf322f048575b1e742c0710be375f9c947cafcae5b316a8","first_computed_at":"2026-07-05T12:05:36.856334Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:05:36.856334Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TrSWPikloY9uK7aP6ZwUIFY+KWZQf/6eoaZKqCMRX50XR2KoPT8yZJS/f6017XaeDBdaHuFrIEfFmelr/DBQDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:05:36.856813Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.05146","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a570abb0fca41cefe6f053ed2d202c38206bb9c32c27da91a06949efab93948c","sha256:a49c4101c7c92205b416437c9a29a3804ad956c07654f5f17a398c5e03f37a76"],"state_sha256":"aecb96641ba5b525658bf69a73d884ec73ffed9aa2a3dca4732c43ff4cff52fc"}