{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:HQX6EDCGPETMYK7STY5LOFFURG","short_pith_number":"pith:HQX6EDCG","schema_version":"1.0","canonical_sha256":"3c2fe20c467926cc2bf29e3ab714b489b853282e27abc35ee4f92a0c4b645052","source":{"kind":"arxiv","id":"2507.01645","version":1},"attestation_state":"computed","paper":{"title":"Adapting Language Models to Indonesian Local Languages: An Empirical Study of Language Transferability on Zero-Shot Settings","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Rifki Afina Putri","submitted_at":"2025-07-02T12:17:55Z","abstract_excerpt":"In this paper, we investigate the transferability of pre-trained language models to low-resource Indonesian local languages through the task of sentiment analysis. We evaluate both zero-shot performance and adapter-based transfer on ten local languages using models of different types: a monolingual Indonesian BERT, multilingual models such as mBERT and XLM-R, and a modular adapter-based approach called MAD-X. To better understand model behavior, we group the target languages into three categories: seen (included during pre-training), partially seen (not included but linguistically related to s"},"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":"2507.01645","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-02T12:17:55Z","cross_cats_sorted":[],"title_canon_sha256":"9bcff45bde221c6faa220ee6095434171f9e684fa6799203839fbd64c9885cdf","abstract_canon_sha256":"95e64e4114341b90afc3f1f941dc3be52cfc3e65211f4a415b6731426fd58929"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:30:52.482363Z","signature_b64":"sRrtULUFtJpwccm7MY6bYmXhArivj7uFXHFM8Z5YHtx+DVT24aBTIH2K3inwilP8WkroZ9I4eXubuwXM3eUUDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3c2fe20c467926cc2bf29e3ab714b489b853282e27abc35ee4f92a0c4b645052","last_reissued_at":"2026-07-05T11:30:52.481902Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:30:52.481902Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Adapting Language Models to Indonesian Local Languages: An Empirical Study of Language Transferability on Zero-Shot Settings","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Rifki Afina Putri","submitted_at":"2025-07-02T12:17:55Z","abstract_excerpt":"In this paper, we investigate the transferability of pre-trained language models to low-resource Indonesian local languages through the task of sentiment analysis. We evaluate both zero-shot performance and adapter-based transfer on ten local languages using models of different types: a monolingual Indonesian BERT, multilingual models such as mBERT and XLM-R, and a modular adapter-based approach called MAD-X. To better understand model behavior, we group the target languages into three categories: seen (included during pre-training), partially seen (not included but linguistically related to s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.01645","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2507.01645/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2507.01645","created_at":"2026-07-05T11:30:52.481954+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.01645v1","created_at":"2026-07-05T11:30:52.481954+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.01645","created_at":"2026-07-05T11:30:52.481954+00:00"},{"alias_kind":"pith_short_12","alias_value":"HQX6EDCGPETM","created_at":"2026-07-05T11:30:52.481954+00:00"},{"alias_kind":"pith_short_16","alias_value":"HQX6EDCGPETMYK7S","created_at":"2026-07-05T11:30:52.481954+00:00"},{"alias_kind":"pith_short_8","alias_value":"HQX6EDCG","created_at":"2026-07-05T11:30:52.481954+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/HQX6EDCGPETMYK7STY5LOFFURG","json":"https://pith.science/pith/HQX6EDCGPETMYK7STY5LOFFURG.json","graph_json":"https://pith.science/api/pith-number/HQX6EDCGPETMYK7STY5LOFFURG/graph.json","events_json":"https://pith.science/api/pith-number/HQX6EDCGPETMYK7STY5LOFFURG/events.json","paper":"https://pith.science/paper/HQX6EDCG"},"agent_actions":{"view_html":"https://pith.science/pith/HQX6EDCGPETMYK7STY5LOFFURG","download_json":"https://pith.science/pith/HQX6EDCGPETMYK7STY5LOFFURG.json","view_paper":"https://pith.science/paper/HQX6EDCG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.01645&json=true","fetch_graph":"https://pith.science/api/pith-number/HQX6EDCGPETMYK7STY5LOFFURG/graph.json","fetch_events":"https://pith.science/api/pith-number/HQX6EDCGPETMYK7STY5LOFFURG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HQX6EDCGPETMYK7STY5LOFFURG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HQX6EDCGPETMYK7STY5LOFFURG/action/storage_attestation","attest_author":"https://pith.science/pith/HQX6EDCGPETMYK7STY5LOFFURG/action/author_attestation","sign_citation":"https://pith.science/pith/HQX6EDCGPETMYK7STY5LOFFURG/action/citation_signature","submit_replication":"https://pith.science/pith/HQX6EDCGPETMYK7STY5LOFFURG/action/replication_record"}},"created_at":"2026-07-05T11:30:52.481954+00:00","updated_at":"2026-07-05T11:30:52.481954+00:00"}