{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:JM6NBGHU3CR5Q6KWI5OTG2L6XR","short_pith_number":"pith:JM6NBGHU","canonical_record":{"source":{"id":"1710.10453","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-10-28T12:00:09Z","cross_cats_sorted":[],"title_canon_sha256":"02e2fe87dac837f02c62ae6caf80550e1d55123c747cf057390a9c4ca508d47e","abstract_canon_sha256":"dcb98c9f19772f5b082f136b811064a3f77196452e7c96cec05c518a430b9c57"},"schema_version":"1.0"},"canonical_sha256":"4b3cd098f4d8a3d87956475d33697ebc4ca4d20f8f2601887072052f7950e28b","source":{"kind":"arxiv","id":"1710.10453","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.10453","created_at":"2026-05-18T00:12:24Z"},{"alias_kind":"arxiv_version","alias_value":"1710.10453v2","created_at":"2026-05-18T00:12:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.10453","created_at":"2026-05-18T00:12:24Z"},{"alias_kind":"pith_short_12","alias_value":"JM6NBGHU3CR5","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_16","alias_value":"JM6NBGHU3CR5Q6KW","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_8","alias_value":"JM6NBGHU","created_at":"2026-05-18T12:31:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:JM6NBGHU3CR5Q6KWI5OTG2L6XR","target":"record","payload":{"canonical_record":{"source":{"id":"1710.10453","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-10-28T12:00:09Z","cross_cats_sorted":[],"title_canon_sha256":"02e2fe87dac837f02c62ae6caf80550e1d55123c747cf057390a9c4ca508d47e","abstract_canon_sha256":"dcb98c9f19772f5b082f136b811064a3f77196452e7c96cec05c518a430b9c57"},"schema_version":"1.0"},"canonical_sha256":"4b3cd098f4d8a3d87956475d33697ebc4ca4d20f8f2601887072052f7950e28b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:12:24.792651Z","signature_b64":"S8eXXL8ll5qLLIeCXh76mOFsHKLiN5hBS1ueWECOcqH6oT6L+hy2Mo5gYlGq7W/qwlYLA5LGEH/h1A2fEQt4BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4b3cd098f4d8a3d87956475d33697ebc4ca4d20f8f2601887072052f7950e28b","last_reissued_at":"2026-05-18T00:12:24.792025Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:12:24.792025Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1710.10453","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:12:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VuuQydH+RQdYY6aJARnfakpOE+/mULNm84ALqHxhnnHU8shEGS+FSQSFZVABoO1UkDa7vz2I9C0eYI0pFAp9BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T12:14:56.332305Z"},"content_sha256":"2e79bf5ba537616bafa40a242637dadc11249bb94eccadeaebd8fcd5245f8740","schema_version":"1.0","event_id":"sha256:2e79bf5ba537616bafa40a242637dadc11249bb94eccadeaebd8fcd5245f8740"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:JM6NBGHU3CR5Q6KWI5OTG2L6XR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Inducing Regular Grammars Using Recurrent Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Avi Caciularu, Idan Rejwan, Jonathan Berant, Mor Cohen","submitted_at":"2017-10-28T12:00:09Z","abstract_excerpt":"Grammar induction is the task of learning a grammar from a set of examples. Recently, neural networks have been shown to be powerful learning machines that can identify patterns in streams of data. In this work we investigate their effectiveness in inducing a regular grammar from data, without any assumptions about the grammar. We train a recurrent neural network to distinguish between strings that are in or outside a regular language, and utilize an algorithm for extracting the learned finite-state automaton. We apply this method to several regular languages and find unexpected results regard"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.10453","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":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:12:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VCIuB4YuCbM8TCQvbNfEozKdXSI3WE+ruR/wfuURBv7qtCK4tkhg5mKiEvm/JgzF5wOz1K71lSCiFfDyGf/HDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T12:14:56.333061Z"},"content_sha256":"f6ca0172171c0372697cc802bf649391018eb31c3851d2815728c00797666ee7","schema_version":"1.0","event_id":"sha256:f6ca0172171c0372697cc802bf649391018eb31c3851d2815728c00797666ee7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JM6NBGHU3CR5Q6KWI5OTG2L6XR/bundle.json","state_url":"https://pith.science/pith/JM6NBGHU3CR5Q6KWI5OTG2L6XR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JM6NBGHU3CR5Q6KWI5OTG2L6XR/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-30T12:14:56Z","links":{"resolver":"https://pith.science/pith/JM6NBGHU3CR5Q6KWI5OTG2L6XR","bundle":"https://pith.science/pith/JM6NBGHU3CR5Q6KWI5OTG2L6XR/bundle.json","state":"https://pith.science/pith/JM6NBGHU3CR5Q6KWI5OTG2L6XR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JM6NBGHU3CR5Q6KWI5OTG2L6XR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:JM6NBGHU3CR5Q6KWI5OTG2L6XR","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":"dcb98c9f19772f5b082f136b811064a3f77196452e7c96cec05c518a430b9c57","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-10-28T12:00:09Z","title_canon_sha256":"02e2fe87dac837f02c62ae6caf80550e1d55123c747cf057390a9c4ca508d47e"},"schema_version":"1.0","source":{"id":"1710.10453","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.10453","created_at":"2026-05-18T00:12:24Z"},{"alias_kind":"arxiv_version","alias_value":"1710.10453v2","created_at":"2026-05-18T00:12:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.10453","created_at":"2026-05-18T00:12:24Z"},{"alias_kind":"pith_short_12","alias_value":"JM6NBGHU3CR5","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_16","alias_value":"JM6NBGHU3CR5Q6KW","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_8","alias_value":"JM6NBGHU","created_at":"2026-05-18T12:31:24Z"}],"graph_snapshots":[{"event_id":"sha256:f6ca0172171c0372697cc802bf649391018eb31c3851d2815728c00797666ee7","target":"graph","created_at":"2026-05-18T00:12:24Z","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":"Grammar induction is the task of learning a grammar from a set of examples. Recently, neural networks have been shown to be powerful learning machines that can identify patterns in streams of data. In this work we investigate their effectiveness in inducing a regular grammar from data, without any assumptions about the grammar. We train a recurrent neural network to distinguish between strings that are in or outside a regular language, and utilize an algorithm for extracting the learned finite-state automaton. We apply this method to several regular languages and find unexpected results regard","authors_text":"Avi Caciularu, Idan Rejwan, Jonathan Berant, Mor Cohen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-10-28T12:00:09Z","title":"Inducing Regular Grammars Using Recurrent Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.10453","kind":"arxiv","version":2},"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":"sha256:2e79bf5ba537616bafa40a242637dadc11249bb94eccadeaebd8fcd5245f8740","target":"record","created_at":"2026-05-18T00:12:24Z","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":"dcb98c9f19772f5b082f136b811064a3f77196452e7c96cec05c518a430b9c57","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-10-28T12:00:09Z","title_canon_sha256":"02e2fe87dac837f02c62ae6caf80550e1d55123c747cf057390a9c4ca508d47e"},"schema_version":"1.0","source":{"id":"1710.10453","kind":"arxiv","version":2}},"canonical_sha256":"4b3cd098f4d8a3d87956475d33697ebc4ca4d20f8f2601887072052f7950e28b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4b3cd098f4d8a3d87956475d33697ebc4ca4d20f8f2601887072052f7950e28b","first_computed_at":"2026-05-18T00:12:24.792025Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:12:24.792025Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"S8eXXL8ll5qLLIeCXh76mOFsHKLiN5hBS1ueWECOcqH6oT6L+hy2Mo5gYlGq7W/qwlYLA5LGEH/h1A2fEQt4BA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:12:24.792651Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.10453","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2e79bf5ba537616bafa40a242637dadc11249bb94eccadeaebd8fcd5245f8740","sha256:f6ca0172171c0372697cc802bf649391018eb31c3851d2815728c00797666ee7"],"state_sha256":"5f65bca7e49662408f14cfdc17c200ab4a10408af6775c7acaf9770abf97e317"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Eg/PnA7aqXaQ3gC1dtVvDFmVmvz3IA4y/8uc+fCMzCaDZY6p4sijqJ0YJm4tqewYNa3c439FLNUPQMALXCPdCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T12:14:56.337373Z","bundle_sha256":"e48e7354f632ffc54ac5730e368ae4280094fb7cbc8fc0699e46543fbd22baaa"}}