{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:EBHLPJ34OHXHMZWWK7HLVIVKAS","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":"5f99559f5eaa9bac36f5704079952a88839f3abac979c973dc53b39e606af474","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-09-29T02:03:44Z","title_canon_sha256":"52b2c576ee59f38ee36a6b2577753ab3eb9c37660fe788b2f148b151a72fc020"},"schema_version":"1.0","source":{"id":"2509.24181","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.24181","created_at":"2026-07-07T02:18:28Z"},{"alias_kind":"arxiv_version","alias_value":"2509.24181v2","created_at":"2026-07-07T02:18:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.24181","created_at":"2026-07-07T02:18:28Z"},{"alias_kind":"pith_short_12","alias_value":"EBHLPJ34OHXH","created_at":"2026-07-07T02:18:28Z"},{"alias_kind":"pith_short_16","alias_value":"EBHLPJ34OHXHMZWW","created_at":"2026-07-07T02:18:28Z"},{"alias_kind":"pith_short_8","alias_value":"EBHLPJ34","created_at":"2026-07-07T02:18:28Z"}],"graph_snapshots":[{"event_id":"sha256:d5b2add7601a2bdd8ee74d4260e8cd05b70c641b007ffe3bb014c3e7f94f55f5","target":"graph","created_at":"2026-07-07T02:18:28Z","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/2509.24181/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Active learning (AL) aims to build high-quality labeled datasets by iteratively selecting the most informative samples from an unlabeled pool under limited annotation budgets. However, in fine-grained image classification, assessing this informativeness reliably is especially challenging due to subtle differences between classes. In this paper, we introduce a novel active learning method, combining discrepancy-confusion uncertainty and calibration diversity for active fine-grained image classification (DECERN), to effectively perceive the distinctiveness between fine-grained images and evaluat","authors_text":"Xi Yang, Yinghao Jin","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-09-29T02:03:44Z","title":"Combining Discrepancy-Confusion Uncertainty and Calibration Diversity for Active Fine-Grained Image Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.24181","kind":"arxiv","version":2},"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":"sha256:4ef1cb00721660b9a8477d958ecf6ea149d5aae2c756ec2dfd2decc33e7d4b00","target":"record","created_at":"2026-07-07T02:18:28Z","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":"5f99559f5eaa9bac36f5704079952a88839f3abac979c973dc53b39e606af474","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-09-29T02:03:44Z","title_canon_sha256":"52b2c576ee59f38ee36a6b2577753ab3eb9c37660fe788b2f148b151a72fc020"},"schema_version":"1.0","source":{"id":"2509.24181","kind":"arxiv","version":2}},"canonical_sha256":"204eb7a77c71ee7666d657cebaa2aa04b7fdfe94dae544894db5afa8b09c0494","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"204eb7a77c71ee7666d657cebaa2aa04b7fdfe94dae544894db5afa8b09c0494","first_computed_at":"2026-07-07T02:18:28.574822Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-07T02:18:28.574822Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xOHWs4msesmZ+ARNrzwIiA9vXqmeqc9cIXrwm6tUUGr0DUzLLAVR+AymZbW+UePxI+h4LFcvLpntBBhSNZ7KAA==","signature_status":"signed_v1","signed_at":"2026-07-07T02:18:28.575854Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.24181","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4ef1cb00721660b9a8477d958ecf6ea149d5aae2c756ec2dfd2decc33e7d4b00","sha256:d5b2add7601a2bdd8ee74d4260e8cd05b70c641b007ffe3bb014c3e7f94f55f5"],"state_sha256":"b7be77aec57d731bc352cd7e489a92d5c9f9d850f79dc32d2c904ca4ab140f85"}