{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:CXEAQTREFWWQO6VBNEM2RHN73N","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":"8d20b1ae725c8d7ec63f4b14c73876b0caeeb84f7851a5b33f61cb7ee67e0d8e","cross_cats_sorted":["cs.LG","cs.LO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-01-23T14:43:12Z","title_canon_sha256":"5fbaef7f46994806b2e108d33d6b758ede9e432dbf3713eb7d86c3615a4d2edd"},"schema_version":"1.0","source":{"id":"2501.13712","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.13712","created_at":"2026-07-05T10:04:33Z"},{"alias_kind":"arxiv_version","alias_value":"2501.13712v1","created_at":"2026-07-05T10:04:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.13712","created_at":"2026-07-05T10:04:33Z"},{"alias_kind":"pith_short_12","alias_value":"CXEAQTREFWWQ","created_at":"2026-07-05T10:04:33Z"},{"alias_kind":"pith_short_16","alias_value":"CXEAQTREFWWQO6VB","created_at":"2026-07-05T10:04:33Z"},{"alias_kind":"pith_short_8","alias_value":"CXEAQTRE","created_at":"2026-07-05T10:04:33Z"}],"graph_snapshots":[{"event_id":"sha256:b55184d9b8047d3e954f031b84affdd077f1d27a196dc40f5ea86ff4c7cf36b4","target":"graph","created_at":"2026-07-05T10:04:33Z","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/2501.13712/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a novel formalisation of tensor semantics for linear temporal logic on finite traces (LTLf), with formal proofs of correctness carried out in the theorem prover Isabelle/HOL. We demonstrate that this formalisation can be integrated into a neurosymbolic learning process by defining and verifying a differentiable loss function for the LTLf constraints, and automatically generating an implementation that integrates with PyTorch. We show that, by using this loss, the process learns to satisfy pre-specified logical constraints. Our approach offers a fully rigorous framework for constrain","authors_text":"Filip Smola, Jacques D. Fleuriot, Mark Chevallier, Richard Schmoetten","cross_cats":["cs.LG","cs.LO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-01-23T14:43:12Z","title":"Formally Verified Neurosymbolic Trajectory Learning via Tensor-based Linear Temporal Logic on Finite Traces"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.13712","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":"sha256:47c28c6f60e8650f5a944f161335ca54c19cc4a92476c1ee6e5cdbe6ddf0f82d","target":"record","created_at":"2026-07-05T10:04:33Z","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":"8d20b1ae725c8d7ec63f4b14c73876b0caeeb84f7851a5b33f61cb7ee67e0d8e","cross_cats_sorted":["cs.LG","cs.LO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-01-23T14:43:12Z","title_canon_sha256":"5fbaef7f46994806b2e108d33d6b758ede9e432dbf3713eb7d86c3615a4d2edd"},"schema_version":"1.0","source":{"id":"2501.13712","kind":"arxiv","version":1}},"canonical_sha256":"15c8084e242dad077aa16919a89dbfdb63c1b72390d5958077f68e48f9ac004f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"15c8084e242dad077aa16919a89dbfdb63c1b72390d5958077f68e48f9ac004f","first_computed_at":"2026-07-05T10:04:33.056594Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:04:33.056594Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1dWKSHwCwW/n+KquJ+VXqd9gaAbPoYlQPyPE+Sf9yArn62YwjsCcdyM/iAL48LXuBsAaTgYnPjPI/3KL7gIYDg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:04:33.057046Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.13712","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:47c28c6f60e8650f5a944f161335ca54c19cc4a92476c1ee6e5cdbe6ddf0f82d","sha256:b55184d9b8047d3e954f031b84affdd077f1d27a196dc40f5ea86ff4c7cf36b4"],"state_sha256":"cb0a56f20b7b6f82f9e3971c523bb85182211c9b8aa0b26e34df68876cc2f1c9"}