{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:3CHJXHKB4P5R3DPFZYACDO5YM4","short_pith_number":"pith:3CHJXHKB","canonical_record":{"source":{"id":"2607.06949","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-08T03:21:19Z","cross_cats_sorted":[],"title_canon_sha256":"a0c9df214f7c93f9fbd5a8401f65fc4093850e24b59c024f57e65393ea5447f3","abstract_canon_sha256":"1bfbb59196be3c3103c3c393ec7d228eec23d6e2005628647866405f2222e951"},"schema_version":"1.0"},"canonical_sha256":"d88e9b9d41e3fb1d8de5ce0021bbb8673942de6f655dbe4e5aaaf5ecc81cc5b0","source":{"kind":"arxiv","id":"2607.06949","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.06949","created_at":"2026-07-09T00:19:40Z"},{"alias_kind":"arxiv_version","alias_value":"2607.06949v1","created_at":"2026-07-09T00:19:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.06949","created_at":"2026-07-09T00:19:40Z"},{"alias_kind":"pith_short_12","alias_value":"3CHJXHKB4P5R","created_at":"2026-07-09T00:19:40Z"},{"alias_kind":"pith_short_16","alias_value":"3CHJXHKB4P5R3DPF","created_at":"2026-07-09T00:19:40Z"},{"alias_kind":"pith_short_8","alias_value":"3CHJXHKB","created_at":"2026-07-09T00:19:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:3CHJXHKB4P5R3DPFZYACDO5YM4","target":"record","payload":{"canonical_record":{"source":{"id":"2607.06949","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-08T03:21:19Z","cross_cats_sorted":[],"title_canon_sha256":"a0c9df214f7c93f9fbd5a8401f65fc4093850e24b59c024f57e65393ea5447f3","abstract_canon_sha256":"1bfbb59196be3c3103c3c393ec7d228eec23d6e2005628647866405f2222e951"},"schema_version":"1.0"},"canonical_sha256":"d88e9b9d41e3fb1d8de5ce0021bbb8673942de6f655dbe4e5aaaf5ecc81cc5b0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-09T00:19:40.932344Z","signature_b64":"3rwhvGFxc6LBXstbpSpSdP0V2cb7q11otkxuttAY6CpNoILTgBRe/gFJsLBaKfBPAl9H7/R+WRuIwuKQ5+5oAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d88e9b9d41e3fb1d8de5ce0021bbb8673942de6f655dbe4e5aaaf5ecc81cc5b0","last_reissued_at":"2026-07-09T00:19:40.931916Z","signature_status":"signed_v1","first_computed_at":"2026-07-09T00:19:40.931916Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.06949","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":"2026-07-09T00:19:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YSlntCuy0acpEn5cVGiYQi5kOjRYap3wDnAcfDTS6l2OJw17GhfQasRvxA4VDaf1fxHz9c2rL6clDe+Bu61MCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T04:18:17.251690Z"},"content_sha256":"8540895b997fd77b88e147bf255f1cf0ca47e0009823c04d5441e40a20eb2981","schema_version":"1.0","event_id":"sha256:8540895b997fd77b88e147bf255f1cf0ca47e0009823c04d5441e40a20eb2981"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:3CHJXHKB4P5R3DPFZYACDO5YM4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SpiS-GAN: Spiral-Modulated Handwriting Synthesis with Star Operation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dang Hoai Nam, Nguyen Duy Hieu, Pham Hoang Giap, Quang Huu Hieu, Vo Nguyen Le Duy","submitted_at":"2026-07-08T03:21:19Z","abstract_excerpt":"Training robust handwriting recognition (HTR) systems requires massive amounts of annotated data, which is often difficult to acquire. While synthetic handwriting generation offers a practical solution to expand training sets, existing models struggle with several core issues. First, previous approaches, even MLP-based models fail to effectively trace cursive handwriting due to fixed-grid spatial receptive field. Second, their CNN-relied discriminators usually lose structural details through aggressive downsampling, making broken connections difficult to detect. Third, existing architectures a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.06949","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/2607.06949/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":"2026-07-09T00:19:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Irg7D0+u8JQ6prcYZPuFlffL2BjeAS9P3LhuhLsQ6OZTV/9cyA/M0dRLJvNcOcVAuaBzBkbXy8jwcq/J50VGAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T04:18:17.252076Z"},"content_sha256":"db861e5d29a03436baf91e286006fd59e7f3f5f71a36886ef171d0ef7c7fe7b4","schema_version":"1.0","event_id":"sha256:db861e5d29a03436baf91e286006fd59e7f3f5f71a36886ef171d0ef7c7fe7b4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3CHJXHKB4P5R3DPFZYACDO5YM4/bundle.json","state_url":"https://pith.science/pith/3CHJXHKB4P5R3DPFZYACDO5YM4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3CHJXHKB4P5R3DPFZYACDO5YM4/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":"2026-07-28T04:18:17Z","links":{"resolver":"https://pith.science/pith/3CHJXHKB4P5R3DPFZYACDO5YM4","bundle":"https://pith.science/pith/3CHJXHKB4P5R3DPFZYACDO5YM4/bundle.json","state":"https://pith.science/pith/3CHJXHKB4P5R3DPFZYACDO5YM4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3CHJXHKB4P5R3DPFZYACDO5YM4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:3CHJXHKB4P5R3DPFZYACDO5YM4","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":"1bfbb59196be3c3103c3c393ec7d228eec23d6e2005628647866405f2222e951","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-08T03:21:19Z","title_canon_sha256":"a0c9df214f7c93f9fbd5a8401f65fc4093850e24b59c024f57e65393ea5447f3"},"schema_version":"1.0","source":{"id":"2607.06949","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.06949","created_at":"2026-07-09T00:19:40Z"},{"alias_kind":"arxiv_version","alias_value":"2607.06949v1","created_at":"2026-07-09T00:19:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.06949","created_at":"2026-07-09T00:19:40Z"},{"alias_kind":"pith_short_12","alias_value":"3CHJXHKB4P5R","created_at":"2026-07-09T00:19:40Z"},{"alias_kind":"pith_short_16","alias_value":"3CHJXHKB4P5R3DPF","created_at":"2026-07-09T00:19:40Z"},{"alias_kind":"pith_short_8","alias_value":"3CHJXHKB","created_at":"2026-07-09T00:19:40Z"}],"graph_snapshots":[{"event_id":"sha256:db861e5d29a03436baf91e286006fd59e7f3f5f71a36886ef171d0ef7c7fe7b4","target":"graph","created_at":"2026-07-09T00:19:40Z","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/2607.06949/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Training robust handwriting recognition (HTR) systems requires massive amounts of annotated data, which is often difficult to acquire. While synthetic handwriting generation offers a practical solution to expand training sets, existing models struggle with several core issues. First, previous approaches, even MLP-based models fail to effectively trace cursive handwriting due to fixed-grid spatial receptive field. Second, their CNN-relied discriminators usually lose structural details through aggressive downsampling, making broken connections difficult to detect. Third, existing architectures a","authors_text":"Dang Hoai Nam, Nguyen Duy Hieu, Pham Hoang Giap, Quang Huu Hieu, Vo Nguyen Le Duy","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-08T03:21:19Z","title":"SpiS-GAN: Spiral-Modulated Handwriting Synthesis with Star Operation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.06949","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":"sha256:8540895b997fd77b88e147bf255f1cf0ca47e0009823c04d5441e40a20eb2981","target":"record","created_at":"2026-07-09T00:19:40Z","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":"1bfbb59196be3c3103c3c393ec7d228eec23d6e2005628647866405f2222e951","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-08T03:21:19Z","title_canon_sha256":"a0c9df214f7c93f9fbd5a8401f65fc4093850e24b59c024f57e65393ea5447f3"},"schema_version":"1.0","source":{"id":"2607.06949","kind":"arxiv","version":1}},"canonical_sha256":"d88e9b9d41e3fb1d8de5ce0021bbb8673942de6f655dbe4e5aaaf5ecc81cc5b0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d88e9b9d41e3fb1d8de5ce0021bbb8673942de6f655dbe4e5aaaf5ecc81cc5b0","first_computed_at":"2026-07-09T00:19:40.931916Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-09T00:19:40.931916Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3rwhvGFxc6LBXstbpSpSdP0V2cb7q11otkxuttAY6CpNoILTgBRe/gFJsLBaKfBPAl9H7/R+WRuIwuKQ5+5oAw==","signature_status":"signed_v1","signed_at":"2026-07-09T00:19:40.932344Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.06949","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8540895b997fd77b88e147bf255f1cf0ca47e0009823c04d5441e40a20eb2981","sha256:db861e5d29a03436baf91e286006fd59e7f3f5f71a36886ef171d0ef7c7fe7b4"],"state_sha256":"762e1edddd8859e8aa36a3183c181ba38c9fdb80d6a1084b11ce65e3a7535174"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I3eIJWNxHdpIirWHqKmxTneLbe9Vv14O16ryG2xbR78+WY2HIJMBlgXT/dm2fbgCGgYmZOqI8Zzukq2o38DQAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-28T04:18:17.254657Z","bundle_sha256":"e5ed27cda9b3abc887d521691f8ed5d1a0129fc4e44503fd9b97b4b85997687b"}}