{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:656ANMQCBAAKVOFN7SX35N7ARM","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":"15f68838bcd44bbc3fcd530c9c33c0f95dbef7b0fb28c0e9890b99735137f56d","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-23T08:21:21Z","title_canon_sha256":"f2dcf1a77767ae83b5953fcf00ad19f28dd3995b7e679057ea7d59977f954377"},"schema_version":"1.0","source":{"id":"2205.11117","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.11117","created_at":"2026-07-05T09:33:22Z"},{"alias_kind":"arxiv_version","alias_value":"2205.11117v3","created_at":"2026-07-05T09:33:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.11117","created_at":"2026-07-05T09:33:22Z"},{"alias_kind":"pith_short_12","alias_value":"656ANMQCBAAK","created_at":"2026-07-05T09:33:22Z"},{"alias_kind":"pith_short_16","alias_value":"656ANMQCBAAKVOFN","created_at":"2026-07-05T09:33:22Z"},{"alias_kind":"pith_short_8","alias_value":"656ANMQC","created_at":"2026-07-05T09:33:22Z"}],"graph_snapshots":[{"event_id":"sha256:56a8d2c00ce3b8f6e24c1dc5ddcde2087adc6e26835d47a37eb73117dc6d7b76","target":"graph","created_at":"2026-07-05T09:33:22Z","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/2205.11117/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Active learning (AL) is a sub-field of ML focused on the development of methods to iteratively and economically acquire data by strategically querying new data points that are the most useful for a particular task. Here, we introduce PyRelationAL, an open source library for AL research. We describe a modular toolkit based around a two step design methodology for composing pool-based active learning strategies applicable to both single-acquisition and batch-acquisition strategies. This framework allows for the mathematical and practical specification of a broad number of existing and novel stra","authors_text":"Alice Del Vecchio, Alison Pouplin, Jake P. Taylor-King, Jyothish Soman, Lindsay Edwards, Oliver Bolton, Paul Scherer, Suraj M S, Thomas Gaudelet","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-23T08:21:21Z","title":"PyRelationAL: a python library for active learning research and development"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.11117","kind":"arxiv","version":3},"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:dd3f27795cb9468948ae0efffa1a553261a828952e5e5bd0ec3e33648ba18d08","target":"record","created_at":"2026-07-05T09:33:22Z","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":"15f68838bcd44bbc3fcd530c9c33c0f95dbef7b0fb28c0e9890b99735137f56d","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-23T08:21:21Z","title_canon_sha256":"f2dcf1a77767ae83b5953fcf00ad19f28dd3995b7e679057ea7d59977f954377"},"schema_version":"1.0","source":{"id":"2205.11117","kind":"arxiv","version":3}},"canonical_sha256":"f77c06b2020800aab8adfcafbeb7e08b15f8b7ecf62a15bb6c8ede319801aa0c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f77c06b2020800aab8adfcafbeb7e08b15f8b7ecf62a15bb6c8ede319801aa0c","first_computed_at":"2026-07-05T09:33:22.911196Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:33:22.911196Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SMn2KzRQcrvkIy+E/5ALY63FfBcpp4bJTBeSc3LYnr7ZOqayWBfPMr0/ggxDuo0kMoJ/1FvJXgMBlB+l5WnSAg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:33:22.911728Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.11117","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dd3f27795cb9468948ae0efffa1a553261a828952e5e5bd0ec3e33648ba18d08","sha256:56a8d2c00ce3b8f6e24c1dc5ddcde2087adc6e26835d47a37eb73117dc6d7b76"],"state_sha256":"0bcdb3ec635aa96f34ddf0be83f0a680132b1fdb9bac7ea9f59b5ea7a1a47a5b"}