{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:77DID3HJGYHOCUE4IULSFDX4PB","short_pith_number":"pith:77DID3HJ","schema_version":"1.0","canonical_sha256":"ffc681ece9360ee1509c4517228efc787d883e3ca19885c2991d4b80b1173016","source":{"kind":"arxiv","id":"1803.10631","version":1},"attestation_state":"computed","paper":{"title":"Meta-Learning a Dynamical Language Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Clement Delangue, Julien Chaumond, Thomas Wolf","submitted_at":"2018-03-28T14:08:12Z","abstract_excerpt":"We consider the task of word-level language modeling and study the possibility of combining hidden-states-based short-term representations with medium-term representations encoded in dynamical weights of a language model. Our work extends recent experiments on language models with dynamically evolving weights by casting the language modeling problem into an online learning-to-learn framework in which a meta-learner is trained by gradient-descent to continuously update a language model weights."},"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":"1803.10631","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-03-28T14:08:12Z","cross_cats_sorted":[],"title_canon_sha256":"c57a59bfd1638673a315125f666502d8de991a267d2344da1b0d6b0b1fbfa1ff","abstract_canon_sha256":"f3a4e109b1bb231f8756dadf66ad4b4ef3775e8f906234d1c24736b27e84c4f1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:19:54.647311Z","signature_b64":"Vd4ClWCZ2Nz34sdhBAuR/MbLXY3IufT8ZUogEueAZicoYugu61m0EeQM1RDyitH4KQtC2ICp9JYXjhBCedkHBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ffc681ece9360ee1509c4517228efc787d883e3ca19885c2991d4b80b1173016","last_reissued_at":"2026-05-18T00:19:54.646611Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:19:54.646611Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Meta-Learning a Dynamical Language Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Clement Delangue, Julien Chaumond, Thomas Wolf","submitted_at":"2018-03-28T14:08:12Z","abstract_excerpt":"We consider the task of word-level language modeling and study the possibility of combining hidden-states-based short-term representations with medium-term representations encoded in dynamical weights of a language model. Our work extends recent experiments on language models with dynamically evolving weights by casting the language modeling problem into an online learning-to-learn framework in which a meta-learner is trained by gradient-descent to continuously update a language model weights."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.10631","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":"1803.10631","created_at":"2026-05-18T00:19:54.646711+00:00"},{"alias_kind":"arxiv_version","alias_value":"1803.10631v1","created_at":"2026-05-18T00:19:54.646711+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.10631","created_at":"2026-05-18T00:19:54.646711+00:00"},{"alias_kind":"pith_short_12","alias_value":"77DID3HJGYHO","created_at":"2026-05-18T12:32:11.075285+00:00"},{"alias_kind":"pith_short_16","alias_value":"77DID3HJGYHOCUE4","created_at":"2026-05-18T12:32:11.075285+00:00"},{"alias_kind":"pith_short_8","alias_value":"77DID3HJ","created_at":"2026-05-18T12:32:11.075285+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/77DID3HJGYHOCUE4IULSFDX4PB","json":"https://pith.science/pith/77DID3HJGYHOCUE4IULSFDX4PB.json","graph_json":"https://pith.science/api/pith-number/77DID3HJGYHOCUE4IULSFDX4PB/graph.json","events_json":"https://pith.science/api/pith-number/77DID3HJGYHOCUE4IULSFDX4PB/events.json","paper":"https://pith.science/paper/77DID3HJ"},"agent_actions":{"view_html":"https://pith.science/pith/77DID3HJGYHOCUE4IULSFDX4PB","download_json":"https://pith.science/pith/77DID3HJGYHOCUE4IULSFDX4PB.json","view_paper":"https://pith.science/paper/77DID3HJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1803.10631&json=true","fetch_graph":"https://pith.science/api/pith-number/77DID3HJGYHOCUE4IULSFDX4PB/graph.json","fetch_events":"https://pith.science/api/pith-number/77DID3HJGYHOCUE4IULSFDX4PB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/77DID3HJGYHOCUE4IULSFDX4PB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/77DID3HJGYHOCUE4IULSFDX4PB/action/storage_attestation","attest_author":"https://pith.science/pith/77DID3HJGYHOCUE4IULSFDX4PB/action/author_attestation","sign_citation":"https://pith.science/pith/77DID3HJGYHOCUE4IULSFDX4PB/action/citation_signature","submit_replication":"https://pith.science/pith/77DID3HJGYHOCUE4IULSFDX4PB/action/replication_record"}},"created_at":"2026-05-18T00:19:54.646711+00:00","updated_at":"2026-05-18T00:19:54.646711+00:00"}