{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:UZJRYQNJV7VOOETUGHMH3BECFL","short_pith_number":"pith:UZJRYQNJ","schema_version":"1.0","canonical_sha256":"a6531c41a9afeae7127431d87d84822ad385b5ed635dcfedfd3e8badd9926036","source":{"kind":"arxiv","id":"2506.06333","version":2},"attestation_state":"computed","paper":{"title":"Extending AALpy with Passive Learning: A Generalized State-Merging Approach","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.FL"],"primary_cat":"cs.LG","authors_text":"Benjamin von Berg, Bernhard K. Aichernig","submitted_at":"2025-05-31T08:29:32Z","abstract_excerpt":"AALpy is a well-established open-source automata learning library written in Python with a focus on active learning of systems with IO behavior. It provides a wide range of state-of-the-art algorithms for different automaton types ranging from fully deterministic to probabilistic automata. In this work, we present the recent addition of a generalized implementation of an important method from the domain of passive automata learning: state-merging in the red-blue framework. Using a common internal representation for different automaton types allows for a general and highly configurable implemen"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.06333","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-31T08:29:32Z","cross_cats_sorted":["cs.FL"],"title_canon_sha256":"c19793d31c6c48bbbddc9a355352444e2d39784eb9c156cd431a50c628d12013","abstract_canon_sha256":"5af20c22b76f9585f33f046031079c71ac1ab4f6ebc17b0eee14c93be593903f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:20:13.334884Z","signature_b64":"6ARCLEA4IZNa3nNzSWdbxbH/G8ziK3hJnq7B4hDDHGn0szIw0t1e2r4g1gYzv3EwNRzw4g9kWpq+K/VG0BloAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a6531c41a9afeae7127431d87d84822ad385b5ed635dcfedfd3e8badd9926036","last_reissued_at":"2026-07-05T11:20:13.334392Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:20:13.334392Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Extending AALpy with Passive Learning: A Generalized State-Merging Approach","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.FL"],"primary_cat":"cs.LG","authors_text":"Benjamin von Berg, Bernhard K. Aichernig","submitted_at":"2025-05-31T08:29:32Z","abstract_excerpt":"AALpy is a well-established open-source automata learning library written in Python with a focus on active learning of systems with IO behavior. It provides a wide range of state-of-the-art algorithms for different automaton types ranging from fully deterministic to probabilistic automata. In this work, we present the recent addition of a generalized implementation of an important method from the domain of passive automata learning: state-merging in the red-blue framework. Using a common internal representation for different automaton types allows for a general and highly configurable implemen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.06333","kind":"arxiv","version":2},"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/2506.06333/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.06333","created_at":"2026-07-05T11:20:13.334452+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.06333v2","created_at":"2026-07-05T11:20:13.334452+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.06333","created_at":"2026-07-05T11:20:13.334452+00:00"},{"alias_kind":"pith_short_12","alias_value":"UZJRYQNJV7VO","created_at":"2026-07-05T11:20:13.334452+00:00"},{"alias_kind":"pith_short_16","alias_value":"UZJRYQNJV7VOOETU","created_at":"2026-07-05T11:20:13.334452+00:00"},{"alias_kind":"pith_short_8","alias_value":"UZJRYQNJ","created_at":"2026-07-05T11:20:13.334452+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/UZJRYQNJV7VOOETUGHMH3BECFL","json":"https://pith.science/pith/UZJRYQNJV7VOOETUGHMH3BECFL.json","graph_json":"https://pith.science/api/pith-number/UZJRYQNJV7VOOETUGHMH3BECFL/graph.json","events_json":"https://pith.science/api/pith-number/UZJRYQNJV7VOOETUGHMH3BECFL/events.json","paper":"https://pith.science/paper/UZJRYQNJ"},"agent_actions":{"view_html":"https://pith.science/pith/UZJRYQNJV7VOOETUGHMH3BECFL","download_json":"https://pith.science/pith/UZJRYQNJV7VOOETUGHMH3BECFL.json","view_paper":"https://pith.science/paper/UZJRYQNJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.06333&json=true","fetch_graph":"https://pith.science/api/pith-number/UZJRYQNJV7VOOETUGHMH3BECFL/graph.json","fetch_events":"https://pith.science/api/pith-number/UZJRYQNJV7VOOETUGHMH3BECFL/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UZJRYQNJV7VOOETUGHMH3BECFL/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UZJRYQNJV7VOOETUGHMH3BECFL/action/storage_attestation","attest_author":"https://pith.science/pith/UZJRYQNJV7VOOETUGHMH3BECFL/action/author_attestation","sign_citation":"https://pith.science/pith/UZJRYQNJV7VOOETUGHMH3BECFL/action/citation_signature","submit_replication":"https://pith.science/pith/UZJRYQNJV7VOOETUGHMH3BECFL/action/replication_record"}},"created_at":"2026-07-05T11:20:13.334452+00:00","updated_at":"2026-07-05T11:20:13.334452+00:00"}