{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:NRICBAYFR3SSXDV37QS5LRJPF4","short_pith_number":"pith:NRICBAYF","schema_version":"1.0","canonical_sha256":"6c502083058ee52b8ebbfc25d5c52f2f103dd96abe3ac2b02c227863b5df1ab8","source":{"kind":"arxiv","id":"1803.11138","version":1},"attestation_state":"computed","paper":{"title":"Colorless green recurrent networks dream hierarchically","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Edouard Grave, Kristina Gulordava, Marco Baroni, Piotr Bojanowski, Tal Linzen","submitted_at":"2018-03-29T16:27:36Z","abstract_excerpt":"Recurrent neural networks (RNNs) have achieved impressive results in a variety of linguistic processing tasks, suggesting that they can induce non-trivial properties of language. We investigate here to what extent RNNs learn to track abstract hierarchical syntactic structure. We test whether RNNs trained with a generic language modeling objective in four languages (Italian, English, Hebrew, Russian) can predict long-distance number agreement in various constructions. We include in our evaluation nonsensical sentences where RNNs cannot rely on semantic or lexical cues (\"The colorless green idea"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1803.11138","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-03-29T16:27:36Z","cross_cats_sorted":[],"title_canon_sha256":"a49acfafdd3c9442b8d50b165f64a81fd9ad0e61785618a97ffb7576e4cf8bc5","abstract_canon_sha256":"601aa87bf73a6f68470175de03f544bf175db07aeb869b9898ce924e74baf72e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:19:48.405282Z","signature_b64":"oizpkcncg6+BZfpx+S6fQ7rMBPDr1O6SPzWMrCPcFKHGVn0QoZPUz1PnR4E1+ZCXSK9lsIIYXzo26TdQ72M4Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6c502083058ee52b8ebbfc25d5c52f2f103dd96abe3ac2b02c227863b5df1ab8","last_reissued_at":"2026-05-18T00:19:48.404577Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:19:48.404577Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Colorless green recurrent networks dream hierarchically","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Edouard Grave, Kristina Gulordava, Marco Baroni, Piotr Bojanowski, Tal Linzen","submitted_at":"2018-03-29T16:27:36Z","abstract_excerpt":"Recurrent neural networks (RNNs) have achieved impressive results in a variety of linguistic processing tasks, suggesting that they can induce non-trivial properties of language. We investigate here to what extent RNNs learn to track abstract hierarchical syntactic structure. We test whether RNNs trained with a generic language modeling objective in four languages (Italian, English, Hebrew, Russian) can predict long-distance number agreement in various constructions. We include in our evaluation nonsensical sentences where RNNs cannot rely on semantic or lexical cues (\"The colorless green idea"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.11138","kind":"arxiv","version":1},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1803.11138","created_at":"2026-05-18T00:19:48.404682+00:00"},{"alias_kind":"arxiv_version","alias_value":"1803.11138v1","created_at":"2026-05-18T00:19:48.404682+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.11138","created_at":"2026-05-18T00:19:48.404682+00:00"},{"alias_kind":"pith_short_12","alias_value":"NRICBAYFR3SS","created_at":"2026-05-18T12:32:40.477152+00:00"},{"alias_kind":"pith_short_16","alias_value":"NRICBAYFR3SSXDV3","created_at":"2026-05-18T12:32:40.477152+00:00"},{"alias_kind":"pith_short_8","alias_value":"NRICBAYF","created_at":"2026-05-18T12:32:40.477152+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/NRICBAYFR3SSXDV37QS5LRJPF4","json":"https://pith.science/pith/NRICBAYFR3SSXDV37QS5LRJPF4.json","graph_json":"https://pith.science/api/pith-number/NRICBAYFR3SSXDV37QS5LRJPF4/graph.json","events_json":"https://pith.science/api/pith-number/NRICBAYFR3SSXDV37QS5LRJPF4/events.json","paper":"https://pith.science/paper/NRICBAYF"},"agent_actions":{"view_html":"https://pith.science/pith/NRICBAYFR3SSXDV37QS5LRJPF4","download_json":"https://pith.science/pith/NRICBAYFR3SSXDV37QS5LRJPF4.json","view_paper":"https://pith.science/paper/NRICBAYF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1803.11138&json=true","fetch_graph":"https://pith.science/api/pith-number/NRICBAYFR3SSXDV37QS5LRJPF4/graph.json","fetch_events":"https://pith.science/api/pith-number/NRICBAYFR3SSXDV37QS5LRJPF4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NRICBAYFR3SSXDV37QS5LRJPF4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NRICBAYFR3SSXDV37QS5LRJPF4/action/storage_attestation","attest_author":"https://pith.science/pith/NRICBAYFR3SSXDV37QS5LRJPF4/action/author_attestation","sign_citation":"https://pith.science/pith/NRICBAYFR3SSXDV37QS5LRJPF4/action/citation_signature","submit_replication":"https://pith.science/pith/NRICBAYFR3SSXDV37QS5LRJPF4/action/replication_record"}},"created_at":"2026-05-18T00:19:48.404682+00:00","updated_at":"2026-05-18T00:19:48.404682+00:00"}