{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:XI2EJMRMBOA3WFLTE4RJTXOYUW","short_pith_number":"pith:XI2EJMRM","canonical_record":{"source":{"id":"2506.03817","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-04T10:41:37Z","cross_cats_sorted":[],"title_canon_sha256":"98fa592f5cb584864d2de997c5debb0479ac589cbee1a847cc88712e67cb08da","abstract_canon_sha256":"93b925d0589e76861800d22dd9fa37746944aa93ce26935c3ba0f032db56b988"},"schema_version":"1.0"},"canonical_sha256":"ba3444b22c0b81bb1573272299ddd8a59f5028d9b8c5a446fcb872fb719320ce","source":{"kind":"arxiv","id":"2506.03817","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.03817","created_at":"2026-07-05T11:15:52Z"},{"alias_kind":"arxiv_version","alias_value":"2506.03817v1","created_at":"2026-07-05T11:15:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.03817","created_at":"2026-07-05T11:15:52Z"},{"alias_kind":"pith_short_12","alias_value":"XI2EJMRMBOA3","created_at":"2026-07-05T11:15:52Z"},{"alias_kind":"pith_short_16","alias_value":"XI2EJMRMBOA3WFLT","created_at":"2026-07-05T11:15:52Z"},{"alias_kind":"pith_short_8","alias_value":"XI2EJMRM","created_at":"2026-07-05T11:15:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:XI2EJMRMBOA3WFLTE4RJTXOYUW","target":"record","payload":{"canonical_record":{"source":{"id":"2506.03817","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-04T10:41:37Z","cross_cats_sorted":[],"title_canon_sha256":"98fa592f5cb584864d2de997c5debb0479ac589cbee1a847cc88712e67cb08da","abstract_canon_sha256":"93b925d0589e76861800d22dd9fa37746944aa93ce26935c3ba0f032db56b988"},"schema_version":"1.0"},"canonical_sha256":"ba3444b22c0b81bb1573272299ddd8a59f5028d9b8c5a446fcb872fb719320ce","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:15:52.324830Z","signature_b64":"Ru6/3HsDbRPFlkE320rnyiFuBTm0TLY739tnt/6iuBN2YW5UOmOWtK8OiVq5HMyvbdqTeU/A4DbS+vxZl2fmDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ba3444b22c0b81bb1573272299ddd8a59f5028d9b8c5a446fcb872fb719320ce","last_reissued_at":"2026-07-05T11:15:52.324356Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:15:52.324356Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.03817","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:15:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OtF64WHaakEuMvayplHPoM1t5k2PHbnIY+a++EdszGdZtZJvBQ6cHNt2Lz7Opxt2jHaWn1uDdUzo7+4RERctDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:30:58.253805Z"},"content_sha256":"be31e4d799465c521aac5a4f6dd508b39b1f5230a063c8b02ff983ecda31846f","schema_version":"1.0","event_id":"sha256:be31e4d799465c521aac5a4f6dd508b39b1f5230a063c8b02ff983ecda31846f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:XI2EJMRMBOA3WFLTE4RJTXOYUW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Survey of Active Learning Hyperparameters: Insights from a Large-Scale Experimental Grid","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Anja Reusch, Claudio Hartmann, Julius Gonsior, Maik Thiele, Tim Rie{\\ss}, Wolfgang Lehner","submitted_at":"2025-06-04T10:41:37Z","abstract_excerpt":"Annotating data is a time-consuming and costly task, but it is inherently required for supervised machine learning. Active Learning (AL) is an established method that minimizes human labeling effort by iteratively selecting the most informative unlabeled samples for expert annotation, thereby improving the overall classification performance. Even though AL has been known for decades, AL is still rarely used in real-world applications. As indicated in the two community web surveys among the NLP community about AL, two main reasons continue to hold practitioners back from using AL: first, the co"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.03817","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2506.03817/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:15:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GDRU11JdOXjeWgfEObcW+VyvT2xCXe+7OhKwNqKzKS45buuakmtO5cUpyv04FVJTJrsxtimphmTuu2hCvtsgDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:30:58.254331Z"},"content_sha256":"e6d99d4fa2db2c65cf48879ab4da1366e7267fc35ea921cb674ab551b24519e4","schema_version":"1.0","event_id":"sha256:e6d99d4fa2db2c65cf48879ab4da1366e7267fc35ea921cb674ab551b24519e4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XI2EJMRMBOA3WFLTE4RJTXOYUW/bundle.json","state_url":"https://pith.science/pith/XI2EJMRMBOA3WFLTE4RJTXOYUW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XI2EJMRMBOA3WFLTE4RJTXOYUW/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T15:30:58Z","links":{"resolver":"https://pith.science/pith/XI2EJMRMBOA3WFLTE4RJTXOYUW","bundle":"https://pith.science/pith/XI2EJMRMBOA3WFLTE4RJTXOYUW/bundle.json","state":"https://pith.science/pith/XI2EJMRMBOA3WFLTE4RJTXOYUW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XI2EJMRMBOA3WFLTE4RJTXOYUW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XI2EJMRMBOA3WFLTE4RJTXOYUW","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":"93b925d0589e76861800d22dd9fa37746944aa93ce26935c3ba0f032db56b988","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-04T10:41:37Z","title_canon_sha256":"98fa592f5cb584864d2de997c5debb0479ac589cbee1a847cc88712e67cb08da"},"schema_version":"1.0","source":{"id":"2506.03817","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.03817","created_at":"2026-07-05T11:15:52Z"},{"alias_kind":"arxiv_version","alias_value":"2506.03817v1","created_at":"2026-07-05T11:15:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.03817","created_at":"2026-07-05T11:15:52Z"},{"alias_kind":"pith_short_12","alias_value":"XI2EJMRMBOA3","created_at":"2026-07-05T11:15:52Z"},{"alias_kind":"pith_short_16","alias_value":"XI2EJMRMBOA3WFLT","created_at":"2026-07-05T11:15:52Z"},{"alias_kind":"pith_short_8","alias_value":"XI2EJMRM","created_at":"2026-07-05T11:15:52Z"}],"graph_snapshots":[{"event_id":"sha256:e6d99d4fa2db2c65cf48879ab4da1366e7267fc35ea921cb674ab551b24519e4","target":"graph","created_at":"2026-07-05T11:15:52Z","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/2506.03817/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Annotating data is a time-consuming and costly task, but it is inherently required for supervised machine learning. Active Learning (AL) is an established method that minimizes human labeling effort by iteratively selecting the most informative unlabeled samples for expert annotation, thereby improving the overall classification performance. Even though AL has been known for decades, AL is still rarely used in real-world applications. As indicated in the two community web surveys among the NLP community about AL, two main reasons continue to hold practitioners back from using AL: first, the co","authors_text":"Anja Reusch, Claudio Hartmann, Julius Gonsior, Maik Thiele, Tim Rie{\\ss}, Wolfgang Lehner","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-04T10:41:37Z","title":"Survey of Active Learning Hyperparameters: Insights from a Large-Scale Experimental Grid"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.03817","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:be31e4d799465c521aac5a4f6dd508b39b1f5230a063c8b02ff983ecda31846f","target":"record","created_at":"2026-07-05T11:15:52Z","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":"93b925d0589e76861800d22dd9fa37746944aa93ce26935c3ba0f032db56b988","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-04T10:41:37Z","title_canon_sha256":"98fa592f5cb584864d2de997c5debb0479ac589cbee1a847cc88712e67cb08da"},"schema_version":"1.0","source":{"id":"2506.03817","kind":"arxiv","version":1}},"canonical_sha256":"ba3444b22c0b81bb1573272299ddd8a59f5028d9b8c5a446fcb872fb719320ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ba3444b22c0b81bb1573272299ddd8a59f5028d9b8c5a446fcb872fb719320ce","first_computed_at":"2026-07-05T11:15:52.324356Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:15:52.324356Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ru6/3HsDbRPFlkE320rnyiFuBTm0TLY739tnt/6iuBN2YW5UOmOWtK8OiVq5HMyvbdqTeU/A4DbS+vxZl2fmDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:15:52.324830Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.03817","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:be31e4d799465c521aac5a4f6dd508b39b1f5230a063c8b02ff983ecda31846f","sha256:e6d99d4fa2db2c65cf48879ab4da1366e7267fc35ea921cb674ab551b24519e4"],"state_sha256":"5e9dabae8b5b96076550f6d932cd1a1833446139fcf6f69e8f0851e6750a82da"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DbBEPxCVhCYZFZfwjhDEDyGlmMG7KXwzczJt/OkJ18dXTVE5BigBBGRe1DdwOkcl8yZVJpxQ9czz22GwC9iFBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T15:30:58.259582Z","bundle_sha256":"0659a02fb59f2c00389b708d6b9c3c1deb0386f19fb6fa732210cbeb5904fb90"}}