{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:LF3QWPKDTI7NG2KPSGOQ7QNYSW","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":"34d23597243285503f1b7de7bc2ad864f253c5e0104a2d4c44289155ee4cc004","cross_cats_sorted":["cs.CV","cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-08-06T13:47:18Z","title_canon_sha256":"fbaced5eb994c096f084877613df149bce47ede4d5f4e84a35f6afa495c234cf"},"schema_version":"1.0","source":{"id":"2608.06037","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.06037","created_at":"2026-08-07T00:55:09Z"},{"alias_kind":"arxiv_version","alias_value":"2608.06037v1","created_at":"2026-08-07T00:55:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.06037","created_at":"2026-08-07T00:55:09Z"},{"alias_kind":"pith_short_12","alias_value":"LF3QWPKDTI7N","created_at":"2026-08-07T00:55:09Z"},{"alias_kind":"pith_short_16","alias_value":"LF3QWPKDTI7NG2KP","created_at":"2026-08-07T00:55:09Z"},{"alias_kind":"pith_short_8","alias_value":"LF3QWPKD","created_at":"2026-08-07T00:55:09Z"}],"graph_snapshots":[{"event_id":"sha256:be15e2052d34b83cf0b62e81205ff7c2514293022d601226c742bf9fa78a318f","target":"graph","created_at":"2026-08-07T00:55:09Z","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/2608.06037/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Relational inductive biases are essential for capturing structural dependencies among data. This study investigates a dual-level relational framework for image classification, bridging the gap between implicit representation learning and explicit structural modelling. We begin by establishing a baseline using an EfficientNetB3 architecture. To move beyond standard convolutional biases, we adopt a patch-based strategy, employing a convolutional masked autoencoder to learn implicit inter-patch relationships through self-supervised reconstruction. We then extend this approach by incorporating exp","authors_text":"(2) Medical University of Gda\\'nsk), Jakub Buler (1), Maciej Bobowicz (2), Micha{\\l} Grochowski (1) ((1) Gda\\'nsk University of Technology, Rafa{\\l} Buler (1)","cross_cats":["cs.CV","cs.LG","eess.IV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-08-06T13:47:18Z","title":"Integrating Implicit and Explicit Relational Biases through Graph-Based Multiple Instance Learning: A Case Study in Skin Lesion Diagnosis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.06037","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":"sha256:5e94df8a8f1fd7632e48492ce78e3ac95ad344df81e344c9f8d89b236993a988","target":"record","created_at":"2026-08-07T00:55:09Z","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":"34d23597243285503f1b7de7bc2ad864f253c5e0104a2d4c44289155ee4cc004","cross_cats_sorted":["cs.CV","cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-08-06T13:47:18Z","title_canon_sha256":"fbaced5eb994c096f084877613df149bce47ede4d5f4e84a35f6afa495c234cf"},"schema_version":"1.0","source":{"id":"2608.06037","kind":"arxiv","version":1}},"canonical_sha256":"59770b3d439a3ed3694f919d0fc1b895abd820f2e009a5dc17745cd154b5c2a8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"59770b3d439a3ed3694f919d0fc1b895abd820f2e009a5dc17745cd154b5c2a8","first_computed_at":"2026-08-07T00:55:09.539276Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-07T00:55:09.539276Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"68CUjn9NSez0IoUTbnMgZgV9XMfpH8ze+qCOQ22jIlzk3bWBRWx1qT9kUu8tugtWp9JhsZynM+CDUyyZQhOiBQ==","signature_status":"signed_v1","signed_at":"2026-08-07T00:55:09.540651Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.06037","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5e94df8a8f1fd7632e48492ce78e3ac95ad344df81e344c9f8d89b236993a988","sha256:be15e2052d34b83cf0b62e81205ff7c2514293022d601226c742bf9fa78a318f"],"state_sha256":"95ef490cdec98a2a722f397c953669dd7f1a64f5f83a3f304948a4575c8083ec"}