{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:J6CEA5MRQHWPFFKIEGXJVAVZ6G","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":"c711c642527beeaadbc21b786c5cd89c85a5cbfd5a422bef78d7140b1eadad24","cross_cats_sorted":["cs.LG","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-13T14:49:26Z","title_canon_sha256":"7efa08b4860e7011742aa1129a4ac528e62521a50579ad164aaab51a92fa37ff"},"schema_version":"1.0","source":{"id":"2104.06268","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.06268","created_at":"2026-07-05T02:31:30Z"},{"alias_kind":"arxiv_version","alias_value":"2104.06268v1","created_at":"2026-07-05T02:31:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.06268","created_at":"2026-07-05T02:31:30Z"},{"alias_kind":"pith_short_12","alias_value":"J6CEA5MRQHWP","created_at":"2026-07-05T02:31:30Z"},{"alias_kind":"pith_short_16","alias_value":"J6CEA5MRQHWPFFKI","created_at":"2026-07-05T02:31:30Z"},{"alias_kind":"pith_short_8","alias_value":"J6CEA5MR","created_at":"2026-07-05T02:31:30Z"}],"graph_snapshots":[{"event_id":"sha256:2993c323f719883d90470ae1c1ce6ef9d1cd76d79d38c647fa5c5d5c4f86d555","target":"graph","created_at":"2026-07-05T02:31:30Z","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/2104.06268/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this thesis, we address the data scarcity and limitations of linguistic theory by proposing language-agnostic multi-task training methods. First, we introduce a meta-learning-based approach, meta-transfer learning, in which information is judiciously extracted from high-resource monolingual speech data to the code-switching domain. The meta-transfer learning quickly adapts the model to the code-switching task from a number of monolingual tasks by learning to learn in a multi-task learning fashion. Second, we propose a novel multilingual meta-embeddings approach to effectively represent code","authors_text":"Genta Indra Winata","cross_cats":["cs.LG","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-13T14:49:26Z","title":"Multilingual Transfer Learning for Code-Switched Language and Speech Neural Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.06268","kind":"arxiv","version":1},"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":"sha256:6b15b0b7b3efa84d5376ae79bf423c19d3950b6814794448778ab1a0abc83964","target":"record","created_at":"2026-07-05T02:31:30Z","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":"c711c642527beeaadbc21b786c5cd89c85a5cbfd5a422bef78d7140b1eadad24","cross_cats_sorted":["cs.LG","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-13T14:49:26Z","title_canon_sha256":"7efa08b4860e7011742aa1129a4ac528e62521a50579ad164aaab51a92fa37ff"},"schema_version":"1.0","source":{"id":"2104.06268","kind":"arxiv","version":1}},"canonical_sha256":"4f8440759181ecf2954821ae9a82b9f18653d49c14c1e0f339f1bb483cf650b3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4f8440759181ecf2954821ae9a82b9f18653d49c14c1e0f339f1bb483cf650b3","first_computed_at":"2026-07-05T02:31:30.502032Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:31:30.502032Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8d43uZrc5c/ssg9mLlPGGFQDMD/Aj4AciE/mY8bwUV22apAV31EDMQnESp5eRU0dnoWC4S124b92u5bx4nnSAA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:31:30.502513Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.06268","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6b15b0b7b3efa84d5376ae79bf423c19d3950b6814794448778ab1a0abc83964","sha256:2993c323f719883d90470ae1c1ce6ef9d1cd76d79d38c647fa5c5d5c4f86d555"],"state_sha256":"f0a27fe88149a0aa7d4f87de84e5ff14c834dafd6e9817446d818ec669f7738a"}