{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WM7PXOQBPXP7YBDWMYXLZG44UP","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":"68c570e4194c07abe8112af88e6cb725ae441996bc2c00caf2c98cf6c8741731","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-30T22:02:12Z","title_canon_sha256":"3b3b260c1ea5de9d7419baa99bbd562b1b85fc03ec1b238a7f3087efd4175686"},"schema_version":"1.0","source":{"id":"2607.00223","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.00223","created_at":"2026-07-02T00:18:39Z"},{"alias_kind":"arxiv_version","alias_value":"2607.00223v1","created_at":"2026-07-02T00:18:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.00223","created_at":"2026-07-02T00:18:39Z"},{"alias_kind":"pith_short_12","alias_value":"WM7PXOQBPXP7","created_at":"2026-07-02T00:18:39Z"},{"alias_kind":"pith_short_16","alias_value":"WM7PXOQBPXP7YBDW","created_at":"2026-07-02T00:18:39Z"},{"alias_kind":"pith_short_8","alias_value":"WM7PXOQB","created_at":"2026-07-02T00:18:39Z"}],"graph_snapshots":[{"event_id":"sha256:2d3449ae0cafe73ebe251b17ae318688c14ebf0a1b1cc041b59e0af1dbc70568","target":"graph","created_at":"2026-07-02T00:18:39Z","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/2607.00223/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Medical image segmentation is dominated by U-Net-style encoder-decoder architectures. Vision Transformers (ViTs) overcome the limited receptive field of convolutional networks through self-attention, enabling modeling of long-range dependencies. Early ViT-based segmentation methods typically retained U-Net-style decoders because pretrained ViT representations were insufficient to support accurate dense prediction. Recent advances in large-scale pretraining have redefined the representation capability of ViTs, reducing the reliance on U-Net-style decoder architectures in modern vision models. T","authors_text":"Hao Wang, Oana M. Dumitrascu, Wenhui Zhu, Xin Li, Xiwen Chen, Xuanzhao Dong, Yalin Wang, Yanxi Chen, Yujian Xiong","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-30T22:02:12Z","title":"Does Your ViT Still Need U-Net for Segmentation?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.00223","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":"sha256:9d941bd2c0968ec7361674f7cb88ecbbaf237c811a277882eeb76a7ddcb05852","target":"record","created_at":"2026-07-02T00:18:39Z","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":"68c570e4194c07abe8112af88e6cb725ae441996bc2c00caf2c98cf6c8741731","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-30T22:02:12Z","title_canon_sha256":"3b3b260c1ea5de9d7419baa99bbd562b1b85fc03ec1b238a7f3087efd4175686"},"schema_version":"1.0","source":{"id":"2607.00223","kind":"arxiv","version":1}},"canonical_sha256":"b33efbba017ddffc0476662ebc9b9ca3edf1ce808443dd5f585bcbab7c9a861f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b33efbba017ddffc0476662ebc9b9ca3edf1ce808443dd5f585bcbab7c9a861f","first_computed_at":"2026-07-02T00:18:39.872752Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-02T00:18:39.872752Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OUiIKe5yRaoTK+OJnVmRNICLwGXoak4hvsJ5tCZuaTfC3FN805QVKr7y5vSyjxD30JvRYcnpzaxF4Id/YFUODA==","signature_status":"signed_v1","signed_at":"2026-07-02T00:18:39.873804Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.00223","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9d941bd2c0968ec7361674f7cb88ecbbaf237c811a277882eeb76a7ddcb05852","sha256:2d3449ae0cafe73ebe251b17ae318688c14ebf0a1b1cc041b59e0af1dbc70568"],"state_sha256":"46ddb171613adb5c4fa9ce6cc2bef59e8e04c429e1b15d5693f2344706605bfe"}