{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KVBD2UT7IO3HI4BWPU5XZZJMOA","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":"a899b70fe1173224c01f909956752a2819cff8fbe8ca0a8cb8e53c79be373568","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-02-05T18:58:11Z","title_canon_sha256":"016bf420f397a4049990fcf639c0982a8b29ee1d9d7defb06ef41d66c569b017"},"schema_version":"1.0","source":{"id":"2402.03302","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.03302","created_at":"2026-07-05T07:52:44Z"},{"alias_kind":"arxiv_version","alias_value":"2402.03302v2","created_at":"2026-07-05T07:52:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.03302","created_at":"2026-07-05T07:52:44Z"},{"alias_kind":"pith_short_12","alias_value":"KVBD2UT7IO3H","created_at":"2026-07-05T07:52:44Z"},{"alias_kind":"pith_short_16","alias_value":"KVBD2UT7IO3HI4BW","created_at":"2026-07-05T07:52:44Z"},{"alias_kind":"pith_short_8","alias_value":"KVBD2UT7","created_at":"2026-07-05T07:52:44Z"}],"graph_snapshots":[{"event_id":"sha256:3a2307d5a1f0598f41c2922d15831f02f75756ed5075639cb53ebb9bdb0a589c","target":"graph","created_at":"2026-07-05T07:52:44Z","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/2402.03302/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate medical image segmentation demands the integration of multi-scale information, spanning from local features to global dependencies. However, it is challenging for existing methods to model long-range global information, where convolutional neural networks (CNNs) are constrained by their local receptive fields, and vision transformers (ViTs) suffer from high quadratic complexity of their attention mechanism. Recently, Mamba-based models have gained great attention for their impressive ability in long sequence modeling. Several studies have demonstrated that these models can outperform ","authors_text":"Guangming Shi, Hairong Zheng, Hao Yang, Hong-Yu Zhou, Jiarun Liu, Lequan Yu, Shanshan Wang, Shaoting Zhang, Yan Xi, Yizhou Yu, Yong Liang","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-02-05T18:58:11Z","title":"Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.03302","kind":"arxiv","version":2},"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":"sha256:154f25c15edad1da78b45328ea6b88270938afae8808dcb6c70e5071c6a507cf","target":"record","created_at":"2026-07-05T07:52:44Z","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":"a899b70fe1173224c01f909956752a2819cff8fbe8ca0a8cb8e53c79be373568","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-02-05T18:58:11Z","title_canon_sha256":"016bf420f397a4049990fcf639c0982a8b29ee1d9d7defb06ef41d66c569b017"},"schema_version":"1.0","source":{"id":"2402.03302","kind":"arxiv","version":2}},"canonical_sha256":"55423d527f43b67470367d3b7ce52c70078327946c2d52a7b7ca7b46a9da74bd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"55423d527f43b67470367d3b7ce52c70078327946c2d52a7b7ca7b46a9da74bd","first_computed_at":"2026-07-05T07:52:44.301333Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:52:44.301333Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YIFq0P//HfSGo6aCboDgyw/oOc47nRY9N/uQLFHC5TjYW+pwY1qtdbUcf2rzNx+v+D4/ifgTXOPH2ZKEv7l6DA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:52:44.301838Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.03302","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:154f25c15edad1da78b45328ea6b88270938afae8808dcb6c70e5071c6a507cf","sha256:3a2307d5a1f0598f41c2922d15831f02f75756ed5075639cb53ebb9bdb0a589c"],"state_sha256":"bd112ce412ae27c202302edcf2d35eb9d50a73d252267a4dcdaf0feb3b3a6df2"}