{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:ARJHFYMGKYH2JWTNKQOZZP3ATK","short_pith_number":"pith:ARJHFYMG","canonical_record":{"source":{"id":"2109.01982","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-09-05T03:25:23Z","cross_cats_sorted":[],"title_canon_sha256":"c224b131a7f32ad22b1f02dad5c6f7924a7f2b4c4dc9388fb184d793b3243c14","abstract_canon_sha256":"f7ffe01a8bfc67dbef75bdccc5cba3bdbd4361c9322249d81998bb53b5d2e49a"},"schema_version":"1.0"},"canonical_sha256":"045272e186560fa4da6d541d9cbf609ab5b8eee96f7987673f85d9ee43a927d7","source":{"kind":"arxiv","id":"2109.01982","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.01982","created_at":"2026-07-05T05:20:58Z"},{"alias_kind":"arxiv_version","alias_value":"2109.01982v3","created_at":"2026-07-05T05:20:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.01982","created_at":"2026-07-05T05:20:58Z"},{"alias_kind":"pith_short_12","alias_value":"ARJHFYMGKYH2","created_at":"2026-07-05T05:20:58Z"},{"alias_kind":"pith_short_16","alias_value":"ARJHFYMGKYH2JWTN","created_at":"2026-07-05T05:20:58Z"},{"alias_kind":"pith_short_8","alias_value":"ARJHFYMG","created_at":"2026-07-05T05:20:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:ARJHFYMGKYH2JWTNKQOZZP3ATK","target":"record","payload":{"canonical_record":{"source":{"id":"2109.01982","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-09-05T03:25:23Z","cross_cats_sorted":[],"title_canon_sha256":"c224b131a7f32ad22b1f02dad5c6f7924a7f2b4c4dc9388fb184d793b3243c14","abstract_canon_sha256":"f7ffe01a8bfc67dbef75bdccc5cba3bdbd4361c9322249d81998bb53b5d2e49a"},"schema_version":"1.0"},"canonical_sha256":"045272e186560fa4da6d541d9cbf609ab5b8eee96f7987673f85d9ee43a927d7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:20:58.581588Z","signature_b64":"mODDAAcTeTzPtgD+Qazi6W6//j7C8dQSHhPVwjXRpwRi1tiKLzt9U0ShgVFWoT1l/ASFsIbx3bdLCDL4gzfuDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"045272e186560fa4da6d541d9cbf609ab5b8eee96f7987673f85d9ee43a927d7","last_reissued_at":"2026-07-05T05:20:58.581222Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:20:58.581222Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2109.01982","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:20:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z1VdZkgQbX86oELJIkmXyUZ2HkRztaQAJJwSAp0sgkytuCda8ExbxpCMU8amkGM75gdW1dRcDBIf9iSspJNuDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T20:19:03.134724Z"},"content_sha256":"e29c0fac8e3c4a05f88b0637967bc6b9bb9491e6abfb5aa42ab8ea2a6eeff8de","schema_version":"1.0","event_id":"sha256:e29c0fac8e3c4a05f88b0637967bc6b9bb9491e6abfb5aa42ab8ea2a6eeff8de"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:ARJHFYMGKYH2JWTNKQOZZP3ATK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Hierarchical Structures with Differentiable Nondeterministic Stacks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Brian DuSell, David Chiang","submitted_at":"2021-09-05T03:25:23Z","abstract_excerpt":"Learning hierarchical structures in sequential data -- from simple algorithmic patterns to natural language -- in a reliable, generalizable way remains a challenging problem for neural language models. Past work has shown that recurrent neural networks (RNNs) struggle to generalize on held-out algorithmic or syntactic patterns without supervision or some inductive bias. To remedy this, many papers have explored augmenting RNNs with various differentiable stacks, by analogy with finite automata and pushdown automata (PDAs). In this paper, we improve the performance of our recently proposed Nond"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.01982","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2109.01982/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T05:20:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vqBNRB2eJVKbhooJ5ucC4tDyWXq0lu/X53qow7tnNlPiCmk+nNe15dobwdR44PueAm+1UuY4EO3im+3sFeOVCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T20:19:03.135273Z"},"content_sha256":"b9bf666ec36703ff287bab5843e378611990193231271a9a28a35cbf08914f53","schema_version":"1.0","event_id":"sha256:b9bf666ec36703ff287bab5843e378611990193231271a9a28a35cbf08914f53"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ARJHFYMGKYH2JWTNKQOZZP3ATK/bundle.json","state_url":"https://pith.science/pith/ARJHFYMGKYH2JWTNKQOZZP3ATK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ARJHFYMGKYH2JWTNKQOZZP3ATK/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":"2026-08-10T20:19:03Z","links":{"resolver":"https://pith.science/pith/ARJHFYMGKYH2JWTNKQOZZP3ATK","bundle":"https://pith.science/pith/ARJHFYMGKYH2JWTNKQOZZP3ATK/bundle.json","state":"https://pith.science/pith/ARJHFYMGKYH2JWTNKQOZZP3ATK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ARJHFYMGKYH2JWTNKQOZZP3ATK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:ARJHFYMGKYH2JWTNKQOZZP3ATK","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":"f7ffe01a8bfc67dbef75bdccc5cba3bdbd4361c9322249d81998bb53b5d2e49a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-09-05T03:25:23Z","title_canon_sha256":"c224b131a7f32ad22b1f02dad5c6f7924a7f2b4c4dc9388fb184d793b3243c14"},"schema_version":"1.0","source":{"id":"2109.01982","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.01982","created_at":"2026-07-05T05:20:58Z"},{"alias_kind":"arxiv_version","alias_value":"2109.01982v3","created_at":"2026-07-05T05:20:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.01982","created_at":"2026-07-05T05:20:58Z"},{"alias_kind":"pith_short_12","alias_value":"ARJHFYMGKYH2","created_at":"2026-07-05T05:20:58Z"},{"alias_kind":"pith_short_16","alias_value":"ARJHFYMGKYH2JWTN","created_at":"2026-07-05T05:20:58Z"},{"alias_kind":"pith_short_8","alias_value":"ARJHFYMG","created_at":"2026-07-05T05:20:58Z"}],"graph_snapshots":[{"event_id":"sha256:b9bf666ec36703ff287bab5843e378611990193231271a9a28a35cbf08914f53","target":"graph","created_at":"2026-07-05T05:20:58Z","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/2109.01982/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning hierarchical structures in sequential data -- from simple algorithmic patterns to natural language -- in a reliable, generalizable way remains a challenging problem for neural language models. Past work has shown that recurrent neural networks (RNNs) struggle to generalize on held-out algorithmic or syntactic patterns without supervision or some inductive bias. To remedy this, many papers have explored augmenting RNNs with various differentiable stacks, by analogy with finite automata and pushdown automata (PDAs). In this paper, we improve the performance of our recently proposed Nond","authors_text":"Brian DuSell, David Chiang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-09-05T03:25:23Z","title":"Learning Hierarchical Structures with Differentiable Nondeterministic Stacks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.01982","kind":"arxiv","version":3},"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:e29c0fac8e3c4a05f88b0637967bc6b9bb9491e6abfb5aa42ab8ea2a6eeff8de","target":"record","created_at":"2026-07-05T05:20:58Z","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":"f7ffe01a8bfc67dbef75bdccc5cba3bdbd4361c9322249d81998bb53b5d2e49a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-09-05T03:25:23Z","title_canon_sha256":"c224b131a7f32ad22b1f02dad5c6f7924a7f2b4c4dc9388fb184d793b3243c14"},"schema_version":"1.0","source":{"id":"2109.01982","kind":"arxiv","version":3}},"canonical_sha256":"045272e186560fa4da6d541d9cbf609ab5b8eee96f7987673f85d9ee43a927d7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"045272e186560fa4da6d541d9cbf609ab5b8eee96f7987673f85d9ee43a927d7","first_computed_at":"2026-07-05T05:20:58.581222Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:20:58.581222Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mODDAAcTeTzPtgD+Qazi6W6//j7C8dQSHhPVwjXRpwRi1tiKLzt9U0ShgVFWoT1l/ASFsIbx3bdLCDL4gzfuDw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:20:58.581588Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.01982","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e29c0fac8e3c4a05f88b0637967bc6b9bb9491e6abfb5aa42ab8ea2a6eeff8de","sha256:b9bf666ec36703ff287bab5843e378611990193231271a9a28a35cbf08914f53"],"state_sha256":"27d5f67d155699a3886338b54295c19e46abeb27e7c9bb75dcf51f784fd5733f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v1QVghVywiCKdxi52k25plsf21XC8nxAmrMe9eKhcwFIBKlPk/vsgzZXQvnSctxSfUV5Xr3VUnneAom0JsUbCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T20:19:03.141458Z","bundle_sha256":"8945a2021e68d7d5785328aca129d4917ac26e6aadc0793d5567d5d92a185a44"}}