{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:SIJXF5H336U4IKL3PAMLQRPBJV","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":"5d5b88cf105bf39d304ab3e9f5f1e18077fc008d6eea19c77ff2ff5530c0b2ed","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-29T12:56:25Z","title_canon_sha256":"093f3e1706202c9c8e35869b387911fddf481ae48deddf560705b77a3c89f955"},"schema_version":"1.0","source":{"id":"1709.10380","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.10380","created_at":"2026-05-18T00:00:41Z"},{"alias_kind":"arxiv_version","alias_value":"1709.10380v5","created_at":"2026-05-18T00:00:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.10380","created_at":"2026-05-18T00:00:41Z"},{"alias_kind":"pith_short_12","alias_value":"SIJXF5H336U4","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"SIJXF5H336U4IKL3","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"SIJXF5H3","created_at":"2026-05-18T12:31:43Z"}],"graph_snapshots":[{"event_id":"sha256:d748b78dbcd5c073cfd013b6a987e918ac906b7246ba019a64c8d70b892e81db","target":"graph","created_at":"2026-05-18T00:00:41Z","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"},"paper":{"abstract_excerpt":"Rule extraction from black-box models is critical in domains that require model validation before implementation, as can be the case in credit scoring and medical diagnosis. Though already a challenging problem in statistical learning in general, the difficulty is even greater when highly non-linear, recursive models, such as recurrent neural networks (RNNs), are fit to data. Here, we study the extraction of rules from second-order recurrent neural networks trained to recognize the Tomita grammars. We show that production rules can be stably extracted from trained RNNs and that in certain case","authors_text":"Alexander G. Ororbia II, C. Lee Giles, Kaixuan Zhang, Qinglong Wang, Xinyu Xing, Xue Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-29T12:56:25Z","title":"An Empirical Evaluation of Rule Extraction from Recurrent Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.10380","kind":"arxiv","version":5},"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:b0520c9ab0ce6258e87557f2cda0b9e2816b565c02dcac61b5adc57883253469","target":"record","created_at":"2026-05-18T00:00:41Z","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":"5d5b88cf105bf39d304ab3e9f5f1e18077fc008d6eea19c77ff2ff5530c0b2ed","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-29T12:56:25Z","title_canon_sha256":"093f3e1706202c9c8e35869b387911fddf481ae48deddf560705b77a3c89f955"},"schema_version":"1.0","source":{"id":"1709.10380","kind":"arxiv","version":5}},"canonical_sha256":"921372f4fbdfa9c4297b7818b845e14d4d75a697140d1d6db34e90d0478dea2d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"921372f4fbdfa9c4297b7818b845e14d4d75a697140d1d6db34e90d0478dea2d","first_computed_at":"2026-05-18T00:00:41.437936Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:00:41.437936Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fYu8FZz8/XpAqQQhoDH9aKOcDrt9vPSBTTSgdjjE1bNtDnVJP6Mui31yWqRnPRttf+B2WwOp5eFbzRcso+UBDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:00:41.438338Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.10380","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b0520c9ab0ce6258e87557f2cda0b9e2816b565c02dcac61b5adc57883253469","sha256:d748b78dbcd5c073cfd013b6a987e918ac906b7246ba019a64c8d70b892e81db"],"state_sha256":"6537611b31a8ca05f21daf131b35cb4927c7576cad49323fe2d4492d0aee9ae1"}