{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:MBSKPBCC5S2RX7T3CF52XTE2RJ","short_pith_number":"pith:MBSKPBCC","schema_version":"1.0","canonical_sha256":"6064a78442ecb51bfe7b117babcc9a8a69a04482985fd390aa7e58b82952ea3a","source":{"kind":"arxiv","id":"1902.01541","version":2},"attestation_state":"computed","paper":{"title":"The Referential Reader: A Recurrent Entity Network for Anaphora Resolution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Fei Liu, Jacob Eisenstein, Luke Zettlemoyer","submitted_at":"2019-02-05T04:41:55Z","abstract_excerpt":"We present a new architecture for storing and accessing entity mentions during online text processing. While reading the text, entity references are identified, and may be stored by either updating or overwriting a cell in a fixed-length memory. The update operation implies coreference with the other mentions that are stored in the same cell; the overwrite operation causes these mentions to be forgotten. By encoding the memory operations as differentiable gates, it is possible to train the model end-to-end, using both a supervised anaphora resolution objective as well as a supplementary langua"},"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":"1902.01541","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-02-05T04:41:55Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"2dbeb44f48560dffd195547ec5af0b476b2c82694387b80febd3983726563d92","abstract_canon_sha256":"21edf1ed678cf112d42fea70498cc48630af5c9a2d5be546b58966b9b296e940"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:12.126593Z","signature_b64":"OmZkztqOY4eJa0UkYN8XIflTDic1RAYaMjF2CTIsKXaCkZCpesQG6ZmuXfvY6JgNGA2RowoQtveURBUEcpP1AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6064a78442ecb51bfe7b117babcc9a8a69a04482985fd390aa7e58b82952ea3a","last_reissued_at":"2026-05-17T23:41:12.126065Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:12.126065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The Referential Reader: A Recurrent Entity Network for Anaphora Resolution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Fei Liu, Jacob Eisenstein, Luke Zettlemoyer","submitted_at":"2019-02-05T04:41:55Z","abstract_excerpt":"We present a new architecture for storing and accessing entity mentions during online text processing. While reading the text, entity references are identified, and may be stored by either updating or overwriting a cell in a fixed-length memory. The update operation implies coreference with the other mentions that are stored in the same cell; the overwrite operation causes these mentions to be forgotten. By encoding the memory operations as differentiable gates, it is possible to train the model end-to-end, using both a supervised anaphora resolution objective as well as a supplementary langua"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.01541","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1902.01541","created_at":"2026-05-17T23:41:12.126152+00:00"},{"alias_kind":"arxiv_version","alias_value":"1902.01541v2","created_at":"2026-05-17T23:41:12.126152+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.01541","created_at":"2026-05-17T23:41:12.126152+00:00"},{"alias_kind":"pith_short_12","alias_value":"MBSKPBCC5S2R","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_16","alias_value":"MBSKPBCC5S2RX7T3","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_8","alias_value":"MBSKPBCC","created_at":"2026-05-18T12:33:21.387695+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"1908.09091","citing_title":"BERT for Coreference Resolution: Baselines and Analysis","ref_index":14,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/MBSKPBCC5S2RX7T3CF52XTE2RJ","json":"https://pith.science/pith/MBSKPBCC5S2RX7T3CF52XTE2RJ.json","graph_json":"https://pith.science/api/pith-number/MBSKPBCC5S2RX7T3CF52XTE2RJ/graph.json","events_json":"https://pith.science/api/pith-number/MBSKPBCC5S2RX7T3CF52XTE2RJ/events.json","paper":"https://pith.science/paper/MBSKPBCC"},"agent_actions":{"view_html":"https://pith.science/pith/MBSKPBCC5S2RX7T3CF52XTE2RJ","download_json":"https://pith.science/pith/MBSKPBCC5S2RX7T3CF52XTE2RJ.json","view_paper":"https://pith.science/paper/MBSKPBCC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1902.01541&json=true","fetch_graph":"https://pith.science/api/pith-number/MBSKPBCC5S2RX7T3CF52XTE2RJ/graph.json","fetch_events":"https://pith.science/api/pith-number/MBSKPBCC5S2RX7T3CF52XTE2RJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MBSKPBCC5S2RX7T3CF52XTE2RJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MBSKPBCC5S2RX7T3CF52XTE2RJ/action/storage_attestation","attest_author":"https://pith.science/pith/MBSKPBCC5S2RX7T3CF52XTE2RJ/action/author_attestation","sign_citation":"https://pith.science/pith/MBSKPBCC5S2RX7T3CF52XTE2RJ/action/citation_signature","submit_replication":"https://pith.science/pith/MBSKPBCC5S2RX7T3CF52XTE2RJ/action/replication_record"}},"created_at":"2026-05-17T23:41:12.126152+00:00","updated_at":"2026-05-17T23:41:12.126152+00:00"}