{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KPD66QI2X3MPBD2CTC5NVJCU5W","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":"712760b991a8e403de8565683dac1aa4ba0f0550113a98813aa696cefe64e5f5","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-03-12T02:28:29Z","title_canon_sha256":"f918ab831be825442adde57e1dd168ece90a6a59ee201478d20d2af964b6dcb5"},"schema_version":"1.0","source":{"id":"2403.07951","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.07951","created_at":"2026-07-05T07:55:32Z"},{"alias_kind":"arxiv_version","alias_value":"2403.07951v1","created_at":"2026-07-05T07:55:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.07951","created_at":"2026-07-05T07:55:32Z"},{"alias_kind":"pith_short_12","alias_value":"KPD66QI2X3MP","created_at":"2026-07-05T07:55:32Z"},{"alias_kind":"pith_short_16","alias_value":"KPD66QI2X3MPBD2C","created_at":"2026-07-05T07:55:32Z"},{"alias_kind":"pith_short_8","alias_value":"KPD66QI2","created_at":"2026-07-05T07:55:32Z"}],"graph_snapshots":[{"event_id":"sha256:b44a4ee1e16ecaf9cf1faf39ece3ce3176632e9aad46ed217c54b669e14f8e39","target":"graph","created_at":"2026-07-05T07:55:32Z","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/2403.07951/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"It has been shown that traditional deep learning methods for electronic microscopy segmentation usually suffer from low transferability when samples and annotations are limited, while large-scale vision foundation models are more robust when transferring between different domains but facing sub-optimal improvement under fine-tuning. In this work, we present a new few-shot domain adaptation framework SAMDA, which combines the Segment Anything Model(SAM) with nnUNet in the embedding space to achieve high transferability and accuracy. Specifically, we choose the Unet-based network as the \"expert\"","authors_text":"Li Xiao, Yiran Wang","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-03-12T02:28:29Z","title":"SAMDA: Leveraging SAM on Few-Shot Domain Adaptation for Electronic Microscopy Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.07951","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:c522abe960fb910f329ba00810dfbff4bfb1f1c87c7bcf7f55fb322cdb557beb","target":"record","created_at":"2026-07-05T07:55:32Z","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":"712760b991a8e403de8565683dac1aa4ba0f0550113a98813aa696cefe64e5f5","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-03-12T02:28:29Z","title_canon_sha256":"f918ab831be825442adde57e1dd168ece90a6a59ee201478d20d2af964b6dcb5"},"schema_version":"1.0","source":{"id":"2403.07951","kind":"arxiv","version":1}},"canonical_sha256":"53c7ef411abed8f08f4298badaa454edb246081ce81118c4bdfdf54d770516c9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"53c7ef411abed8f08f4298badaa454edb246081ce81118c4bdfdf54d770516c9","first_computed_at":"2026-07-05T07:55:32.577757Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:55:32.577757Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"J4FPUG1+oGXG+AfKQMJA2BOgM/mgowNhbkcIX1iwOWjUeMBURhaD9x/kJC8N5fNWhXz2kxPbAXX0l93w72ZkBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:55:32.578164Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.07951","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c522abe960fb910f329ba00810dfbff4bfb1f1c87c7bcf7f55fb322cdb557beb","sha256:b44a4ee1e16ecaf9cf1faf39ece3ce3176632e9aad46ed217c54b669e14f8e39"],"state_sha256":"2869df0c4ca6b64feb89df990f13d358d871f0fbb1dda41a938b9d5db149787e"}