{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:RY7XO7ADBWH6WTD2XCKTZZTSER","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":"459eef46b64831547143248c05921b568bbd22cef01978df4b7ede4ef36e35ea","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-08T16:16:43Z","title_canon_sha256":"0078a1e16773b0100d4160704d66faf26b2b179dbc1eea275b20b11de19f4697"},"schema_version":"1.0","source":{"id":"2508.06429","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.06429","created_at":"2026-07-05T11:50:56Z"},{"alias_kind":"arxiv_version","alias_value":"2508.06429v1","created_at":"2026-07-05T11:50:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.06429","created_at":"2026-07-05T11:50:56Z"},{"alias_kind":"pith_short_12","alias_value":"RY7XO7ADBWH6","created_at":"2026-07-05T11:50:56Z"},{"alias_kind":"pith_short_16","alias_value":"RY7XO7ADBWH6WTD2","created_at":"2026-07-05T11:50:56Z"},{"alias_kind":"pith_short_8","alias_value":"RY7XO7AD","created_at":"2026-07-05T11:50:56Z"}],"graph_snapshots":[{"event_id":"sha256:38c22d1945913c2466e84326767dfc83dd511e1f69714a34517702afd5dedccf","target":"graph","created_at":"2026-07-05T11:50:56Z","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/2508.06429/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning has revolutionized medical imaging, but its effectiveness is severely limited by insufficient labeled training data. This paper introduces a novel GAN-based semi-supervised learning framework specifically designed for low labeled-data regimes, evaluated across settings with 5 to 50 labeled samples per class. Our approach integrates three specialized neural networks -- a generator for class-conditioned image translation, a discriminator for authenticity assessment and classification, and a dedicated classifier -- within a three-phase training framework. The method alternates betwe","authors_text":"Clemente Lauretti, Guido Manni, Loredana Zollo, Paolo Soda","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-08T16:16:43Z","title":"SPARSE Data, Rich Results: Few-Shot Semi-Supervised Learning via Class-Conditioned Image Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.06429","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":"sha256:8322093a1e4d842dd8cdb851919bdc34e4c49879532445e6d0674af01edc3dfc","target":"record","created_at":"2026-07-05T11:50:56Z","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":"459eef46b64831547143248c05921b568bbd22cef01978df4b7ede4ef36e35ea","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-08T16:16:43Z","title_canon_sha256":"0078a1e16773b0100d4160704d66faf26b2b179dbc1eea275b20b11de19f4697"},"schema_version":"1.0","source":{"id":"2508.06429","kind":"arxiv","version":1}},"canonical_sha256":"8e3f777c030d8feb4c7ab8953ce672246f91f34a18bd21efee22e9c3ad7fbd31","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8e3f777c030d8feb4c7ab8953ce672246f91f34a18bd21efee22e9c3ad7fbd31","first_computed_at":"2026-07-05T11:50:56.263193Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:50:56.263193Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oAhWtDMA7Pgc4MyW+eHzQ/60rpUZbn3oWNUtHJKshIoSQE4iz9b2ngyTF0B8+xS5zbBGtzGyKwVbUZAJYlwbCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:50:56.263939Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.06429","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8322093a1e4d842dd8cdb851919bdc34e4c49879532445e6d0674af01edc3dfc","sha256:38c22d1945913c2466e84326767dfc83dd511e1f69714a34517702afd5dedccf"],"state_sha256":"c20919e8f6e91981e54ce3d897125789a029a832eee26352cc8998c584a07fb5"}