{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:AQNKUF4IVFSYC3IMNQBGKASTVV","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":"b95a1e2d2100661e0eb0d2a8fa5926d31736292175541deb048c0efa57ed399e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-17T15:46:09Z","title_canon_sha256":"4b1f5ab74929b0fd00221ccf89a7572959f4d2692bf738890f8238ba22fa6383"},"schema_version":"1.0","source":{"id":"2311.10591","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.10591","created_at":"2026-07-05T07:13:54Z"},{"alias_kind":"arxiv_version","alias_value":"2311.10591v1","created_at":"2026-07-05T07:13:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.10591","created_at":"2026-07-05T07:13:54Z"},{"alias_kind":"pith_short_12","alias_value":"AQNKUF4IVFSY","created_at":"2026-07-05T07:13:54Z"},{"alias_kind":"pith_short_16","alias_value":"AQNKUF4IVFSYC3IM","created_at":"2026-07-05T07:13:54Z"},{"alias_kind":"pith_short_8","alias_value":"AQNKUF4I","created_at":"2026-07-05T07:13:54Z"}],"graph_snapshots":[{"event_id":"sha256:e2de87912affca5351a2206a783acbb2858f8832fa999dfd3e1b65f6fa0a0550","target":"graph","created_at":"2026-07-05T07:13:54Z","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/2311.10591/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we introduce the FOCAL (Ford-OLIVES Collaboration on Active Learning) dataset which enables the study of the impact of annotation-cost within a video active learning setting. Annotation-cost refers to the time it takes an annotator to label and quality-assure a given video sequence. A practical motivation for active learning research is to minimize annotation-cost by selectively labeling informative samples that will maximize performance within a given budget constraint. However, previous work in video active learning lacks real-time annotation labels for accurately assessing co","authors_text":"Chen Zhou, Enrique Corona, Ghassan AlRegib, Kiran Kokilepersaud, Kunjan Singh, Mohit Prabhushankar, Mostafa Parchami, Ryan Benkert, Yash-yee Logan","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-17T15:46:09Z","title":"FOCAL: A Cost-Aware Video Dataset for Active Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.10591","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:e35b9fc5c1e78af5100342c43fceb1aaefebc8ba6095a9990b72f2bff80747d0","target":"record","created_at":"2026-07-05T07:13:54Z","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":"b95a1e2d2100661e0eb0d2a8fa5926d31736292175541deb048c0efa57ed399e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-17T15:46:09Z","title_canon_sha256":"4b1f5ab74929b0fd00221ccf89a7572959f4d2692bf738890f8238ba22fa6383"},"schema_version":"1.0","source":{"id":"2311.10591","kind":"arxiv","version":1}},"canonical_sha256":"041aaa1788a965816d0c6c02650253ad64a7adacf142828e8e500e0bbb25a987","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"041aaa1788a965816d0c6c02650253ad64a7adacf142828e8e500e0bbb25a987","first_computed_at":"2026-07-05T07:13:54.476200Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:13:54.476200Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"syEfJHsiyYhAIHZDT7c0wnVmuQlFRe7AfIbP56ncYQVNpDVkOSeh9WVRW5FlFRZeg5eGo1rbDOyzeVOh4/uYDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:13:54.476586Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.10591","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e35b9fc5c1e78af5100342c43fceb1aaefebc8ba6095a9990b72f2bff80747d0","sha256:e2de87912affca5351a2206a783acbb2858f8832fa999dfd3e1b65f6fa0a0550"],"state_sha256":"cc387370dc5d9bec79e0fbe5ef81f4f5e63928bc934f6dd094949ee5e83df146"}