{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:BIIIABORRNTKGD4HZVPSNUXZPM","short_pith_number":"pith:BIIIABOR","canonical_record":{"source":{"id":"2404.13134","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2024-04-19T18:52:07Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"aa4eedc7c4bdd4ddd5e859487a6c7cbaf5547c8de60f1de670502dee9e272822","abstract_canon_sha256":"d8b35e33909d67fb554dbcbeb4ecbef658501e1a8c5c8aa1c06ff26a14c017a1"},"schema_version":"1.0"},"canonical_sha256":"0a108005d18b66a30f87cd5f26d2f97b06e297767250d49067b15e4724f373ed","source":{"kind":"arxiv","id":"2404.13134","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.13134","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"arxiv_version","alias_value":"2404.13134v1","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.13134","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_12","alias_value":"BIIIABORRNTK","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_16","alias_value":"BIIIABORRNTKGD4H","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_8","alias_value":"BIIIABOR","created_at":"2026-07-05T08:10:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:BIIIABORRNTKGD4HZVPSNUXZPM","target":"record","payload":{"canonical_record":{"source":{"id":"2404.13134","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2024-04-19T18:52:07Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"aa4eedc7c4bdd4ddd5e859487a6c7cbaf5547c8de60f1de670502dee9e272822","abstract_canon_sha256":"d8b35e33909d67fb554dbcbeb4ecbef658501e1a8c5c8aa1c06ff26a14c017a1"},"schema_version":"1.0"},"canonical_sha256":"0a108005d18b66a30f87cd5f26d2f97b06e297767250d49067b15e4724f373ed","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:10:27.878056Z","signature_b64":"ElQt2vD97GKoMGh8PdIAy27a1eFXBIYALIQy8a/cqkr41G4ZS7WBAUObTYqunVfubeR4B4PavmwoXUyeEA7eCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0a108005d18b66a30f87cd5f26d2f97b06e297767250d49067b15e4724f373ed","last_reissued_at":"2026-07-05T08:10:27.877586Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:10:27.877586Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.13134","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:10:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"22huWtzWZGyoBoupk74ZGUSCEJt47sHykXPN35zXDXYPF/RU3/BvHq6mBLucDBF80ytH6fGl9//k698viBFUCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T07:21:04.677393Z"},"content_sha256":"1515eab34316b53528fff268e55a3c20584bfaa44737650e419f639c961866f8","schema_version":"1.0","event_id":"sha256:1515eab34316b53528fff268e55a3c20584bfaa44737650e419f639c961866f8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:BIIIABORRNTKGD4HZVPSNUXZPM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Learning-based Text-in-Image Watermarking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"cs.MM","authors_text":"Bishwa Karki, Chun-Hua Tsai, Pei-Chi Huang, Xin Zhong","submitted_at":"2024-04-19T18:52:07Z","abstract_excerpt":"In this work, we introduce a novel deep learning-based approach to text-in-image watermarking, a method that embeds and extracts textual information within images to enhance data security and integrity. Leveraging the capabilities of deep learning, specifically through the use of Transformer-based architectures for text processing and Vision Transformers for image feature extraction, our method sets new benchmarks in the domain. The proposed method represents the first application of deep learning in text-in-image watermarking that improves adaptivity, allowing the model to intelligently adjus"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.13134","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/2404.13134/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:10:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yXv9QjLWfV3jCF8BTbbFXrz38UzMWT7DwEKXnneLYT7bf+U3zXdgc2n7YYNw+Rh0lEBIhBj8pmLNx+1S7X/kBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T07:21:04.677933Z"},"content_sha256":"21e1143b8f3f7062dfc5d10598f39c650d9effcc7dc7d6602ad148e76bb2c138","schema_version":"1.0","event_id":"sha256:21e1143b8f3f7062dfc5d10598f39c650d9effcc7dc7d6602ad148e76bb2c138"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BIIIABORRNTKGD4HZVPSNUXZPM/bundle.json","state_url":"https://pith.science/pith/BIIIABORRNTKGD4HZVPSNUXZPM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BIIIABORRNTKGD4HZVPSNUXZPM/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-08T07:21:04Z","links":{"resolver":"https://pith.science/pith/BIIIABORRNTKGD4HZVPSNUXZPM","bundle":"https://pith.science/pith/BIIIABORRNTKGD4HZVPSNUXZPM/bundle.json","state":"https://pith.science/pith/BIIIABORRNTKGD4HZVPSNUXZPM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BIIIABORRNTKGD4HZVPSNUXZPM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BIIIABORRNTKGD4HZVPSNUXZPM","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":"d8b35e33909d67fb554dbcbeb4ecbef658501e1a8c5c8aa1c06ff26a14c017a1","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2024-04-19T18:52:07Z","title_canon_sha256":"aa4eedc7c4bdd4ddd5e859487a6c7cbaf5547c8de60f1de670502dee9e272822"},"schema_version":"1.0","source":{"id":"2404.13134","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.13134","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"arxiv_version","alias_value":"2404.13134v1","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.13134","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_12","alias_value":"BIIIABORRNTK","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_16","alias_value":"BIIIABORRNTKGD4H","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_8","alias_value":"BIIIABOR","created_at":"2026-07-05T08:10:27Z"}],"graph_snapshots":[{"event_id":"sha256:21e1143b8f3f7062dfc5d10598f39c650d9effcc7dc7d6602ad148e76bb2c138","target":"graph","created_at":"2026-07-05T08:10:27Z","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/2404.13134/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work, we introduce a novel deep learning-based approach to text-in-image watermarking, a method that embeds and extracts textual information within images to enhance data security and integrity. Leveraging the capabilities of deep learning, specifically through the use of Transformer-based architectures for text processing and Vision Transformers for image feature extraction, our method sets new benchmarks in the domain. The proposed method represents the first application of deep learning in text-in-image watermarking that improves adaptivity, allowing the model to intelligently adjus","authors_text":"Bishwa Karki, Chun-Hua Tsai, Pei-Chi Huang, Xin Zhong","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2024-04-19T18:52:07Z","title":"Deep Learning-based Text-in-Image Watermarking"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.13134","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":"sha256:1515eab34316b53528fff268e55a3c20584bfaa44737650e419f639c961866f8","target":"record","created_at":"2026-07-05T08:10:27Z","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":"d8b35e33909d67fb554dbcbeb4ecbef658501e1a8c5c8aa1c06ff26a14c017a1","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2024-04-19T18:52:07Z","title_canon_sha256":"aa4eedc7c4bdd4ddd5e859487a6c7cbaf5547c8de60f1de670502dee9e272822"},"schema_version":"1.0","source":{"id":"2404.13134","kind":"arxiv","version":1}},"canonical_sha256":"0a108005d18b66a30f87cd5f26d2f97b06e297767250d49067b15e4724f373ed","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0a108005d18b66a30f87cd5f26d2f97b06e297767250d49067b15e4724f373ed","first_computed_at":"2026-07-05T08:10:27.877586Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:10:27.877586Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ElQt2vD97GKoMGh8PdIAy27a1eFXBIYALIQy8a/cqkr41G4ZS7WBAUObTYqunVfubeR4B4PavmwoXUyeEA7eCw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:10:27.878056Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.13134","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1515eab34316b53528fff268e55a3c20584bfaa44737650e419f639c961866f8","sha256:21e1143b8f3f7062dfc5d10598f39c650d9effcc7dc7d6602ad148e76bb2c138"],"state_sha256":"5515b025c1e9052125e8c6cbd0514917375047f68a262fb0e1bea418d518737e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yEPPmazT13bBK+Ws4qE13awOA5zPmk2kjiA1M60tnqXFEZ2os/P1v5NHrjTBO/Lk3v1UF7rJR1jcnw7eBcBjAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T07:21:04.682163Z","bundle_sha256":"32736558b4d8d54329f90392da4478c617046a1ce7fa700a6b5b57002328688e"}}