{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KZH6EKFBS7ILI3PO2VX2JIPT5N","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":"f89a50787b05decb8e0db51ce7f520c22cc463897a9dba513ef295f875621686","cross_cats_sorted":["cs.LG","cs.LO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.FL","submitted_at":"2024-11-15T21:51:14Z","title_canon_sha256":"5a6d77ac8e98eb6baf02b9ece6721022899f908504823909985f92b7bf675fa1"},"schema_version":"1.0","source":{"id":"2411.10601","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.10601","created_at":"2026-07-05T09:36:19Z"},{"alias_kind":"arxiv_version","alias_value":"2411.10601v1","created_at":"2026-07-05T09:36:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.10601","created_at":"2026-07-05T09:36:19Z"},{"alias_kind":"pith_short_12","alias_value":"KZH6EKFBS7IL","created_at":"2026-07-05T09:36:19Z"},{"alias_kind":"pith_short_16","alias_value":"KZH6EKFBS7ILI3PO","created_at":"2026-07-05T09:36:19Z"},{"alias_kind":"pith_short_8","alias_value":"KZH6EKFB","created_at":"2026-07-05T09:36:19Z"}],"graph_snapshots":[{"event_id":"sha256:ed562fe911bd3b9997288870f12c7334e5d20ba19bbffbd19f4ffeea4aedab24","target":"graph","created_at":"2026-07-05T09:36:19Z","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/2411.10601/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Quantitative automata are useful representations for numerous applications, including modeling probability distributions over sequences to Markov chains and reward machines. Actively learning such automata typically occurs using explicitly gathered input-output examples under adaptations of the L-star algorithm. However, obtaining explicit input-output pairs can be expensive, and there exist scenarios, including preference-based learning or learning from rankings, where providing constraints is a less exerting and a more natural way to concisely describe desired properties. Consequently, we pr","authors_text":"Eric Hsiung, Joydeep Biswas, Swarat Chaudhuri","cross_cats":["cs.LG","cs.LO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.FL","submitted_at":"2024-11-15T21:51:14Z","title":"Learning Quantitative Automata Modulo Theories"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.10601","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:eb70bbe35574483f1a70bc0a04a8140d822142689512368c71a9b0714ccc5dcd","target":"record","created_at":"2026-07-05T09:36:19Z","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":"f89a50787b05decb8e0db51ce7f520c22cc463897a9dba513ef295f875621686","cross_cats_sorted":["cs.LG","cs.LO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.FL","submitted_at":"2024-11-15T21:51:14Z","title_canon_sha256":"5a6d77ac8e98eb6baf02b9ece6721022899f908504823909985f92b7bf675fa1"},"schema_version":"1.0","source":{"id":"2411.10601","kind":"arxiv","version":1}},"canonical_sha256":"564fe228a197d0b46deed56fa4a1f3eb7b7c3a7198f75ae651d1d7dee1222823","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"564fe228a197d0b46deed56fa4a1f3eb7b7c3a7198f75ae651d1d7dee1222823","first_computed_at":"2026-07-05T09:36:19.132102Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:36:19.132102Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NipRatcT/5KdEbjoT+MFTQ/YhpHyuscZXV7PgXE95ck53OWUGHIMcnbTEmQO072tvYU/6uYZtiVp39mmMx+3Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:36:19.132527Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.10601","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eb70bbe35574483f1a70bc0a04a8140d822142689512368c71a9b0714ccc5dcd","sha256:ed562fe911bd3b9997288870f12c7334e5d20ba19bbffbd19f4ffeea4aedab24"],"state_sha256":"6bccab1c2e2c15460949007536e6c1f3971179dbeb6ef4872d133cccedc1932e"}