{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:IMXEZ4UTX4O7NJJPLMGUNYDAHI","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":"07c22290c2736f610a69521361cfeed48f4f2864183f48dde1bc956e0fa9519c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-10-14T14:51:13Z","title_canon_sha256":"c6e1cdcc5fffe0e8a3972ce41152a322f10d9abc8c826678b7d5fa0947495c6e"},"schema_version":"1.0","source":{"id":"2410.10576","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.10576","created_at":"2026-07-05T09:20:18Z"},{"alias_kind":"arxiv_version","alias_value":"2410.10576v1","created_at":"2026-07-05T09:20:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.10576","created_at":"2026-07-05T09:20:18Z"},{"alias_kind":"pith_short_12","alias_value":"IMXEZ4UTX4O7","created_at":"2026-07-05T09:20:18Z"},{"alias_kind":"pith_short_16","alias_value":"IMXEZ4UTX4O7NJJP","created_at":"2026-07-05T09:20:18Z"},{"alias_kind":"pith_short_8","alias_value":"IMXEZ4UT","created_at":"2026-07-05T09:20:18Z"}],"graph_snapshots":[{"event_id":"sha256:152a379f4c4be4bbbd46c52d007fbbca2cdf5b1bef25ba5e353e15a4fe9e8399","target":"graph","created_at":"2026-07-05T09:20:18Z","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/2410.10576/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"POS tagging plays a fundamental role in numerous applications. While POS taggers are highly accurate in well-resourced settings, they lag behind in cases of limited or missing training data. This paper focuses on POS tagging for languages with limited data. We seek to identify the characteristics of datasets that make them favourable for training POS tagging models without using any labelled training data from the target language. This is a zero-shot approach. We compare the accuracies of a multilingual large language model (mBERT) fine-tuned on one or more languages related to the target lang","authors_text":"Lukas Vermeire, Miryam de Lhoneux, Zeno Vandenbulcke","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-10-14T14:51:13Z","title":"Recipe for Zero-shot POS Tagging: Is It Useful in Realistic Scenarios?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.10576","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:f7050d29c4e81ec719be656672e14b9be52feb583a02928f877f4c7cdcf879ea","target":"record","created_at":"2026-07-05T09:20:18Z","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":"07c22290c2736f610a69521361cfeed48f4f2864183f48dde1bc956e0fa9519c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-10-14T14:51:13Z","title_canon_sha256":"c6e1cdcc5fffe0e8a3972ce41152a322f10d9abc8c826678b7d5fa0947495c6e"},"schema_version":"1.0","source":{"id":"2410.10576","kind":"arxiv","version":1}},"canonical_sha256":"432e4cf293bf1df6a52f5b0d46e0603a1bd44bd40da40d5a16f94eba3306ec98","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"432e4cf293bf1df6a52f5b0d46e0603a1bd44bd40da40d5a16f94eba3306ec98","first_computed_at":"2026-07-05T09:20:18.263343Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:20:18.263343Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QXf1jJNyA6G9fPL/cOsbqo0DoCwSiDfpm9nUBi2MkuT/CrxmPY2hmjddlGcfMux5afESOZ8p8+XW9hmZrlVUBg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:20:18.263827Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.10576","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f7050d29c4e81ec719be656672e14b9be52feb583a02928f877f4c7cdcf879ea","sha256:152a379f4c4be4bbbd46c52d007fbbca2cdf5b1bef25ba5e353e15a4fe9e8399"],"state_sha256":"ee2f77d2095cf0f720c7697e5a0a7a043d29a1f4b4ebc6a9d243468ec8651455"}