{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:XC2YYF6RTXECDAFIUC7V4WSQ7M","short_pith_number":"pith:XC2YYF6R","schema_version":"1.0","canonical_sha256":"b8b58c17d19dc82180a8a0bf5e5a50fb28614bfe12302261fc80b805552aa123","source":{"kind":"arxiv","id":"1904.05542","version":1},"attestation_state":"computed","paper":{"title":"Scalable Cross-Lingual Transfer of Neural Sentence Embeddings","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Hanan Aldarmaki, Mona Diab","submitted_at":"2019-04-11T05:41:27Z","abstract_excerpt":"We develop and investigate several cross-lingual alignment approaches for neural sentence embedding models, such as the supervised inference classifier, InferSent, and sequential encoder-decoder models. We evaluate three alignment frameworks applied to these models: joint modeling, representation transfer learning, and sentence mapping, using parallel text to guide the alignment. Our results support representation transfer as a scalable approach for modular cross-lingual alignment of neural sentence embeddings, where we observe better performance compared to joint models in intrinsic and extri"},"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":"1904.05542","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-11T05:41:27Z","cross_cats_sorted":[],"title_canon_sha256":"b8e911a830fc449053a07822badfcb9ca4f24fb68e41d5a1b64ae1bb61e4a924","abstract_canon_sha256":"03f2a6ed7a8c3d4f7ba7d7554284b5c64468ace652b220ae7cc741d6551eab5b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:49.209600Z","signature_b64":"x4HDD95ituy0Qluu/ZMhh/s+hQ/wc+Bd3kHjrkXbW/qvt012DFCrV5/XLCF+CBdOgm9HTw+lrLuRpip6QTa0BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b8b58c17d19dc82180a8a0bf5e5a50fb28614bfe12302261fc80b805552aa123","last_reissued_at":"2026-05-17T23:48:49.208778Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:49.208778Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Scalable Cross-Lingual Transfer of Neural Sentence Embeddings","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Hanan Aldarmaki, Mona Diab","submitted_at":"2019-04-11T05:41:27Z","abstract_excerpt":"We develop and investigate several cross-lingual alignment approaches for neural sentence embedding models, such as the supervised inference classifier, InferSent, and sequential encoder-decoder models. We evaluate three alignment frameworks applied to these models: joint modeling, representation transfer learning, and sentence mapping, using parallel text to guide the alignment. Our results support representation transfer as a scalable approach for modular cross-lingual alignment of neural sentence embeddings, where we observe better performance compared to joint models in intrinsic and extri"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.05542","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":"1904.05542","created_at":"2026-05-17T23:48:49.208877+00:00"},{"alias_kind":"arxiv_version","alias_value":"1904.05542v1","created_at":"2026-05-17T23:48:49.208877+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.05542","created_at":"2026-05-17T23:48:49.208877+00:00"},{"alias_kind":"pith_short_12","alias_value":"XC2YYF6RTXEC","created_at":"2026-05-18T12:33:33.725879+00:00"},{"alias_kind":"pith_short_16","alias_value":"XC2YYF6RTXECDAFI","created_at":"2026-05-18T12:33:33.725879+00:00"},{"alias_kind":"pith_short_8","alias_value":"XC2YYF6R","created_at":"2026-05-18T12:33:33.725879+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/XC2YYF6RTXECDAFIUC7V4WSQ7M","json":"https://pith.science/pith/XC2YYF6RTXECDAFIUC7V4WSQ7M.json","graph_json":"https://pith.science/api/pith-number/XC2YYF6RTXECDAFIUC7V4WSQ7M/graph.json","events_json":"https://pith.science/api/pith-number/XC2YYF6RTXECDAFIUC7V4WSQ7M/events.json","paper":"https://pith.science/paper/XC2YYF6R"},"agent_actions":{"view_html":"https://pith.science/pith/XC2YYF6RTXECDAFIUC7V4WSQ7M","download_json":"https://pith.science/pith/XC2YYF6RTXECDAFIUC7V4WSQ7M.json","view_paper":"https://pith.science/paper/XC2YYF6R","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1904.05542&json=true","fetch_graph":"https://pith.science/api/pith-number/XC2YYF6RTXECDAFIUC7V4WSQ7M/graph.json","fetch_events":"https://pith.science/api/pith-number/XC2YYF6RTXECDAFIUC7V4WSQ7M/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XC2YYF6RTXECDAFIUC7V4WSQ7M/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XC2YYF6RTXECDAFIUC7V4WSQ7M/action/storage_attestation","attest_author":"https://pith.science/pith/XC2YYF6RTXECDAFIUC7V4WSQ7M/action/author_attestation","sign_citation":"https://pith.science/pith/XC2YYF6RTXECDAFIUC7V4WSQ7M/action/citation_signature","submit_replication":"https://pith.science/pith/XC2YYF6RTXECDAFIUC7V4WSQ7M/action/replication_record"}},"created_at":"2026-05-17T23:48:49.208877+00:00","updated_at":"2026-05-17T23:48:49.208877+00:00"}