{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:EXVKABVLDSWC3CT23EMUVSLSH3","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":"2824f644575a81482976ccd497ccf7c8fe93fbcb6ce58a9d8f129976a669cc8a","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-07-22T00:30:44Z","title_canon_sha256":"ec620c5143249a4eab5c78ab5a5300dfcf863f37c98b86914216c2eeb3339617"},"schema_version":"1.0","source":{"id":"2507.16122","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.16122","created_at":"2026-07-05T11:43:14Z"},{"alias_kind":"arxiv_version","alias_value":"2507.16122v3","created_at":"2026-07-05T11:43:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.16122","created_at":"2026-07-05T11:43:14Z"},{"alias_kind":"pith_short_12","alias_value":"EXVKABVLDSWC","created_at":"2026-07-05T11:43:14Z"},{"alias_kind":"pith_short_16","alias_value":"EXVKABVLDSWC3CT2","created_at":"2026-07-05T11:43:14Z"},{"alias_kind":"pith_short_8","alias_value":"EXVKABVL","created_at":"2026-07-05T11:43:14Z"}],"graph_snapshots":[{"event_id":"sha256:6b199f96fde859f7ef966a508dee2abc8ed2944d429f61473083a8b8ee87cafa","target":"graph","created_at":"2026-07-05T11:43:14Z","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/2507.16122/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate and efficient medical image segmentation is crucial but challenging due to anatomical variability and high computational demands on volumetric data. Recent hybrid CNN-Transformer architectures achieve state-of-the-art results but add significant complexity. In this paper, we propose MLRU++, a Multiscale Lightweight Residual UNETR++ architecture designed to balance segmentation accuracy and computational efficiency. It introduces two key innovations: a Lightweight Channel and Bottleneck Attention Module (LCBAM) that enhances contextual feature encoding with minimal overhead, and a Mult","authors_text":"Biomedical, Department of Computer Science, KC Santosh (AI Research Lab, Nand Kumar Yadav, Rodrigue Rizk, Sanford School of Medicine, SD, Translational Sciences, University of South Dakota, USA), Vermillion, William CW Chen","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-07-22T00:30:44Z","title":"MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.16122","kind":"arxiv","version":3},"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":"sha256:20d31d43f30f74c09a034f9bc09ac7a7ec5bc468673056d807d6255b0ee0f4c6","target":"record","created_at":"2026-07-05T11:43:14Z","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":"2824f644575a81482976ccd497ccf7c8fe93fbcb6ce58a9d8f129976a669cc8a","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-07-22T00:30:44Z","title_canon_sha256":"ec620c5143249a4eab5c78ab5a5300dfcf863f37c98b86914216c2eeb3339617"},"schema_version":"1.0","source":{"id":"2507.16122","kind":"arxiv","version":3}},"canonical_sha256":"25eaa006ab1cac2d8a7ad9194ac9723ef2acc74f23a01ea01814aa24de654be8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"25eaa006ab1cac2d8a7ad9194ac9723ef2acc74f23a01ea01814aa24de654be8","first_computed_at":"2026-07-05T11:43:14.181930Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:43:14.181930Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NPdc9r3Uqb4y7lIWn7qLhC9LkreNMwEkQLbvWGqnd524f/NOC2Dg5HG9i770t4UroAT7KmO2/QuJNN9ca9lzDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:43:14.182424Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.16122","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:20d31d43f30f74c09a034f9bc09ac7a7ec5bc468673056d807d6255b0ee0f4c6","sha256:6b199f96fde859f7ef966a508dee2abc8ed2944d429f61473083a8b8ee87cafa"],"state_sha256":"0198c661a578c0f33ebda289a8422e39fa00fe22036213fae92194b0f9b05ec0"}