{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:POLQO7VMAZUD6D4KETNBMZLSVK","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":"63d9c21cb6a0b7ceb1075d75233127a460b9db6a01e87cc8a0f6ddc2f4477eba","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.FL","submitted_at":"2022-06-20T08:11:19Z","title_canon_sha256":"db652111ecad083ee7e14bdcd3409fced69405f040931d3105c9c051bded9185"},"schema_version":"1.0","source":{"id":"2206.09619","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.09619","created_at":"2026-07-05T04:33:09Z"},{"alias_kind":"arxiv_version","alias_value":"2206.09619v1","created_at":"2026-07-05T04:33:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.09619","created_at":"2026-07-05T04:33:09Z"},{"alias_kind":"pith_short_12","alias_value":"POLQO7VMAZUD","created_at":"2026-07-05T04:33:09Z"},{"alias_kind":"pith_short_16","alias_value":"POLQO7VMAZUD6D4K","created_at":"2026-07-05T04:33:09Z"},{"alias_kind":"pith_short_8","alias_value":"POLQO7VM","created_at":"2026-07-05T04:33:09Z"}],"graph_snapshots":[{"event_id":"sha256:91680ed72fe48c92a81627740400670280c873a79980e04d20f3a2af088cee68","target":"graph","created_at":"2026-07-05T04:33:09Z","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/2206.09619/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"B\\\"uchi Automata on infinite words present many interesting problems and are used frequently in program verification and model checking. A lot of these problems on B\\\"uchi automata are computationally hard, raising the question if a learning-based data-driven analysis might be more efficient than using traditional algorithms. Since B\\\"uchi automata can be represented by graphs, graph neural networks are a natural choice for such a learning-based analysis. In this paper, we demonstrate how graph neural networks can be used to reliably predict basic properties of B\\\"uchi automata when trained on","authors_text":"Andreas Fischer, Christophe Stammet, Prisca Dotti, Ulrich Ultes-Nitsche","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.FL","submitted_at":"2022-06-20T08:11:19Z","title":"Analyzing B\\\"uchi Automata with Graph Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.09619","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":"sha256:6489de6fcd6a65e6663b1337eca97837bc53b5ff3ac4a47b3c400a54ad93cfda","target":"record","created_at":"2026-07-05T04:33:09Z","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":"63d9c21cb6a0b7ceb1075d75233127a460b9db6a01e87cc8a0f6ddc2f4477eba","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.FL","submitted_at":"2022-06-20T08:11:19Z","title_canon_sha256":"db652111ecad083ee7e14bdcd3409fced69405f040931d3105c9c051bded9185"},"schema_version":"1.0","source":{"id":"2206.09619","kind":"arxiv","version":1}},"canonical_sha256":"7b97077eac06683f0f8a24da166572aa9736dd870928e97bad65beb92d9253c1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7b97077eac06683f0f8a24da166572aa9736dd870928e97bad65beb92d9253c1","first_computed_at":"2026-07-05T04:33:09.290507Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:33:09.290507Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"V0IfkCkfrhYpenRu3J4YnF/5LCopGLJTq98wLJbCdAeHsfwMb7xUKgBXalLx4RZH8OaMT0n+h2K0mbc3BzFdDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:33:09.290939Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.09619","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6489de6fcd6a65e6663b1337eca97837bc53b5ff3ac4a47b3c400a54ad93cfda","sha256:91680ed72fe48c92a81627740400670280c873a79980e04d20f3a2af088cee68"],"state_sha256":"0716d37b4dc3abf18c97e20d4be5d766a1f1101b0f3c6334d9d0825b40bf644d"}