{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:3IXJYAA7MF5P355L5P4K5WP5CQ","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":"6755b75b87fb44c16eb2f7944502bb1dfbc47133594fef9807c11e418f6c8a3d","cross_cats_sorted":["cs.AI","cs.CV","physics.ao-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-13T06:41:37Z","title_canon_sha256":"ffff1ffaeaa90ba1383e338cb632ad5cdc7371c4f35bbb2ce78aa92642ee528b"},"schema_version":"1.0","source":{"id":"2403.10555","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.10555","created_at":"2026-07-05T07:57:03Z"},{"alias_kind":"arxiv_version","alias_value":"2403.10555v1","created_at":"2026-07-05T07:57:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.10555","created_at":"2026-07-05T07:57:03Z"},{"alias_kind":"pith_short_12","alias_value":"3IXJYAA7MF5P","created_at":"2026-07-05T07:57:03Z"},{"alias_kind":"pith_short_16","alias_value":"3IXJYAA7MF5P355L","created_at":"2026-07-05T07:57:03Z"},{"alias_kind":"pith_short_8","alias_value":"3IXJYAA7","created_at":"2026-07-05T07:57:03Z"}],"graph_snapshots":[{"event_id":"sha256:d5b1489aab84c5efe89c098f7de4b401704514e365f13542453bb43fe0426bd6","target":"graph","created_at":"2026-07-05T07:57:03Z","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/2403.10555/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning-based, data-driven models are gaining prevalence in climate research, particularly for global weather prediction. However, training the global weather data at high resolution requires massive computational resources. Therefore, we present a new model named KARINA to overcome the substantial computational demands typical of this field. This model achieves forecasting accuracy comparable to higher-resolution counterparts with significantly less computational resources, requiring only 4 NVIDIA A100 GPUs and less than 12 hours of training. KARINA combines ConvNext, SENet, and Geocycl","authors_text":"Daehyun Kang, Jeong-Gil Lee, Minjong Cheon, Seon-Yu Kang, Yo-Hwan Choi, Yumi Choi","cross_cats":["cs.AI","cs.CV","physics.ao-ph"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-13T06:41:37Z","title":"KARINA: An Efficient Deep Learning Model for Global Weather Forecast"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.10555","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":"sha256:28f3d0db06e7e08e0de6068fdb46a8122fe355238f796da5bf9c910f87687a1b","target":"record","created_at":"2026-07-05T07:57:03Z","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":"6755b75b87fb44c16eb2f7944502bb1dfbc47133594fef9807c11e418f6c8a3d","cross_cats_sorted":["cs.AI","cs.CV","physics.ao-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-13T06:41:37Z","title_canon_sha256":"ffff1ffaeaa90ba1383e338cb632ad5cdc7371c4f35bbb2ce78aa92642ee528b"},"schema_version":"1.0","source":{"id":"2403.10555","kind":"arxiv","version":1}},"canonical_sha256":"da2e9c001f617afdf7abebf8aed9fd140cc67c504e2c2fcf4bceb71d6444dbad","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"da2e9c001f617afdf7abebf8aed9fd140cc67c504e2c2fcf4bceb71d6444dbad","first_computed_at":"2026-07-05T07:57:03.006378Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:57:03.006378Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"29Nr5aJqYPg8uXMJfBiheWGSV1k0qIB/CtdpFOfBXpvWfIbAMVOltHw9GkPwFwthoqgrV0tgjKDu7OOVaItrBw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:57:03.006769Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.10555","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:28f3d0db06e7e08e0de6068fdb46a8122fe355238f796da5bf9c910f87687a1b","sha256:d5b1489aab84c5efe89c098f7de4b401704514e365f13542453bb43fe0426bd6"],"state_sha256":"a5c2dda0113411e82c7965de6a561a76394a3df6234d7491416bc065bf186e81"}