{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:57ZP7XPEGJSRJQ5U5LFAVIQANA","short_pith_number":"pith:57ZP7XPE","canonical_record":{"source":{"id":"2208.01252","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-08-02T05:04:53Z","cross_cats_sorted":[],"title_canon_sha256":"b6d6da398abfac94f274705556e3c2c93e2b33211bb0d57998eff6e43b72043a","abstract_canon_sha256":"91043e0e2b6b30dfbf634cdcc7978fcda6ec6126af4d9afdfe88cb99cfbd6034"},"schema_version":"1.0"},"canonical_sha256":"eff2ffdde4326514c3b4eaca0aa200680f028a647d069875918726bd03fe3e81","source":{"kind":"arxiv","id":"2208.01252","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.01252","created_at":"2026-07-05T04:45:31Z"},{"alias_kind":"arxiv_version","alias_value":"2208.01252v1","created_at":"2026-07-05T04:45:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.01252","created_at":"2026-07-05T04:45:31Z"},{"alias_kind":"pith_short_12","alias_value":"57ZP7XPEGJSR","created_at":"2026-07-05T04:45:31Z"},{"alias_kind":"pith_short_16","alias_value":"57ZP7XPEGJSRJQ5U","created_at":"2026-07-05T04:45:31Z"},{"alias_kind":"pith_short_8","alias_value":"57ZP7XPE","created_at":"2026-07-05T04:45:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:57ZP7XPEGJSRJQ5U5LFAVIQANA","target":"record","payload":{"canonical_record":{"source":{"id":"2208.01252","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-08-02T05:04:53Z","cross_cats_sorted":[],"title_canon_sha256":"b6d6da398abfac94f274705556e3c2c93e2b33211bb0d57998eff6e43b72043a","abstract_canon_sha256":"91043e0e2b6b30dfbf634cdcc7978fcda6ec6126af4d9afdfe88cb99cfbd6034"},"schema_version":"1.0"},"canonical_sha256":"eff2ffdde4326514c3b4eaca0aa200680f028a647d069875918726bd03fe3e81","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:45:31.420157Z","signature_b64":"teUDRWNwFtkx0FRuGkAdukxr/qT/WxT2vwh5jzJGT+Gf3BH1b/3OWbcdYq++nkMaShGLII4GUjvJ2yOyQp8cDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eff2ffdde4326514c3b4eaca0aa200680f028a647d069875918726bd03fe3e81","last_reissued_at":"2026-07-05T04:45:31.419749Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:45:31.419749Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2208.01252","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":"2026-07-05T04:45:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/LKn+6tv1/8gUY2d6/dUZ40RZBS4bVTs32dt176eM0ytT5u67CuwvBG6oUXNrO3jFnI7/8c+a5VxMPD1UxiDCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-26T12:20:11.458145Z"},"content_sha256":"b21aaadbd1a45f04121992275ae7057a47a8b3a2b0fcd06692ce39a90db20d74","schema_version":"1.0","event_id":"sha256:b21aaadbd1a45f04121992275ae7057a47a8b3a2b0fcd06692ce39a90db20d74"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:57ZP7XPEGJSRJQ5U5LFAVIQANA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Novel Transformer Network with Shifted Window Cross-Attention for Spatiotemporal Weather Forecasting","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alabi Bojesomo, Hasan Al Marzouqi, Panos Liatsis","submitted_at":"2022-08-02T05:04:53Z","abstract_excerpt":"Earth Observatory is a growing research area that can capitalize on the powers of AI for short time forecasting, a Now-casting scenario. In this work, we tackle the challenge of weather forecasting using a video transformer network. Vision transformer architectures have been explored in various applications, with major constraints being the computational complexity of Attention and the data hungry training. To address these issues, we propose the use of Video Swin-Transformer, coupled with a dedicated augmentation scheme. Moreover, we employ gradual spatial reduction on the encoder side and cr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.01252","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/2208.01252/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":"2026-07-05T04:45:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Qs5WUQ8tYi/8kfXxaAWagI0NpLohJwiVlHO3mBAhirCKaVb4uckzQMR6GWOWZHopcTrgcJyb0YR/URP/KAJBCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-26T12:20:11.458544Z"},"content_sha256":"daa3093876697c5154828ddfceaa0ba1cd0dff67ed3049aca0d478d3cb6cabbc","schema_version":"1.0","event_id":"sha256:daa3093876697c5154828ddfceaa0ba1cd0dff67ed3049aca0d478d3cb6cabbc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/57ZP7XPEGJSRJQ5U5LFAVIQANA/bundle.json","state_url":"https://pith.science/pith/57ZP7XPEGJSRJQ5U5LFAVIQANA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/57ZP7XPEGJSRJQ5U5LFAVIQANA/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":"2026-07-26T12:20:11Z","links":{"resolver":"https://pith.science/pith/57ZP7XPEGJSRJQ5U5LFAVIQANA","bundle":"https://pith.science/pith/57ZP7XPEGJSRJQ5U5LFAVIQANA/bundle.json","state":"https://pith.science/pith/57ZP7XPEGJSRJQ5U5LFAVIQANA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/57ZP7XPEGJSRJQ5U5LFAVIQANA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:57ZP7XPEGJSRJQ5U5LFAVIQANA","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":"91043e0e2b6b30dfbf634cdcc7978fcda6ec6126af4d9afdfe88cb99cfbd6034","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-08-02T05:04:53Z","title_canon_sha256":"b6d6da398abfac94f274705556e3c2c93e2b33211bb0d57998eff6e43b72043a"},"schema_version":"1.0","source":{"id":"2208.01252","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.01252","created_at":"2026-07-05T04:45:31Z"},{"alias_kind":"arxiv_version","alias_value":"2208.01252v1","created_at":"2026-07-05T04:45:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.01252","created_at":"2026-07-05T04:45:31Z"},{"alias_kind":"pith_short_12","alias_value":"57ZP7XPEGJSR","created_at":"2026-07-05T04:45:31Z"},{"alias_kind":"pith_short_16","alias_value":"57ZP7XPEGJSRJQ5U","created_at":"2026-07-05T04:45:31Z"},{"alias_kind":"pith_short_8","alias_value":"57ZP7XPE","created_at":"2026-07-05T04:45:31Z"}],"graph_snapshots":[{"event_id":"sha256:daa3093876697c5154828ddfceaa0ba1cd0dff67ed3049aca0d478d3cb6cabbc","target":"graph","created_at":"2026-07-05T04:45:31Z","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/2208.01252/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Earth Observatory is a growing research area that can capitalize on the powers of AI for short time forecasting, a Now-casting scenario. In this work, we tackle the challenge of weather forecasting using a video transformer network. Vision transformer architectures have been explored in various applications, with major constraints being the computational complexity of Attention and the data hungry training. To address these issues, we propose the use of Video Swin-Transformer, coupled with a dedicated augmentation scheme. Moreover, we employ gradual spatial reduction on the encoder side and cr","authors_text":"Alabi Bojesomo, Hasan Al Marzouqi, Panos Liatsis","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-08-02T05:04:53Z","title":"A Novel Transformer Network with Shifted Window Cross-Attention for Spatiotemporal Weather Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.01252","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:b21aaadbd1a45f04121992275ae7057a47a8b3a2b0fcd06692ce39a90db20d74","target":"record","created_at":"2026-07-05T04:45:31Z","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":"91043e0e2b6b30dfbf634cdcc7978fcda6ec6126af4d9afdfe88cb99cfbd6034","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-08-02T05:04:53Z","title_canon_sha256":"b6d6da398abfac94f274705556e3c2c93e2b33211bb0d57998eff6e43b72043a"},"schema_version":"1.0","source":{"id":"2208.01252","kind":"arxiv","version":1}},"canonical_sha256":"eff2ffdde4326514c3b4eaca0aa200680f028a647d069875918726bd03fe3e81","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eff2ffdde4326514c3b4eaca0aa200680f028a647d069875918726bd03fe3e81","first_computed_at":"2026-07-05T04:45:31.419749Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:45:31.419749Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"teUDRWNwFtkx0FRuGkAdukxr/qT/WxT2vwh5jzJGT+Gf3BH1b/3OWbcdYq++nkMaShGLII4GUjvJ2yOyQp8cDw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:45:31.420157Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.01252","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b21aaadbd1a45f04121992275ae7057a47a8b3a2b0fcd06692ce39a90db20d74","sha256:daa3093876697c5154828ddfceaa0ba1cd0dff67ed3049aca0d478d3cb6cabbc"],"state_sha256":"d43492cd4a0e163f384635ea054abb3dac25358c2fcd2d9ca52297a809140acb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WFg92bV9KZpdCVC76hdKO2TJvUob3hiR5viv/kkbdeV0Z2OM4IDnvLJ2JL8TPumIvAz0/Po+UzfklyvbNCZcDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-26T12:20:11.460793Z","bundle_sha256":"1939114d1892705ab40d49bfd7fe6c0e0bad5bfc8a9276837ebf3ea3841447ed"}}