{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:LOKYJTYAG66U5CJLWALVF4KUYG","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":"b61c23fce7268647efa8c4772372ac846ff84b1d0078369e292a50730d12493d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-26T05:05:32Z","title_canon_sha256":"1eeadfd3857d01c7600b7bcca784a581499b89c43091e127b9c9a5aaf1d0516a"},"schema_version":"1.0","source":{"id":"2005.12515","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.12515","created_at":"2026-07-05T03:21:05Z"},{"alias_kind":"arxiv_version","alias_value":"2005.12515v2","created_at":"2026-07-05T03:21:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.12515","created_at":"2026-07-05T03:21:05Z"},{"alias_kind":"pith_short_12","alias_value":"LOKYJTYAG66U","created_at":"2026-07-05T03:21:05Z"},{"alias_kind":"pith_short_16","alias_value":"LOKYJTYAG66U5CJL","created_at":"2026-07-05T03:21:05Z"},{"alias_kind":"pith_short_8","alias_value":"LOKYJTYA","created_at":"2026-07-05T03:21:05Z"}],"graph_snapshots":[{"event_id":"sha256:2b40f3095d8d82cee42320bf30529a013f5812b5b529de5920c42b5c2315ac58","target":"graph","created_at":"2026-07-05T03:21:05Z","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/2005.12515/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The surge of pre-trained language models has begun a new era in the field of Natural Language Processing (NLP) by allowing us to build powerful language models. Among these models, Transformer-based models such as BERT have become increasingly popular due to their state-of-the-art performance. However, these models are usually focused on English, leaving other languages to multilingual models with limited resources. This paper proposes a monolingual BERT for the Persian language (ParsBERT), which shows its state-of-the-art performance compared to other architectures and multilingual models. Al","authors_text":"Marzieh Farahani, Mehrdad Farahani, Mohammad Gharachorloo, Mohammad Manthouri","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-26T05:05:32Z","title":"ParsBERT: Transformer-based Model for Persian Language Understanding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.12515","kind":"arxiv","version":2},"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:ec1229af23fa73d8282e40426a8417e88b4a62efb6c946e66c2d0ce938744049","target":"record","created_at":"2026-07-05T03:21:05Z","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":"b61c23fce7268647efa8c4772372ac846ff84b1d0078369e292a50730d12493d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-26T05:05:32Z","title_canon_sha256":"1eeadfd3857d01c7600b7bcca784a581499b89c43091e127b9c9a5aaf1d0516a"},"schema_version":"1.0","source":{"id":"2005.12515","kind":"arxiv","version":2}},"canonical_sha256":"5b9584cf0037bd4e892bb01752f154c1a84df8a8f709c29ee60f150cb37ce08f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5b9584cf0037bd4e892bb01752f154c1a84df8a8f709c29ee60f150cb37ce08f","first_computed_at":"2026-07-05T03:21:05.453570Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:21:05.453570Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qC3CsJNNWkOcKAU4CXd8JpiRTnjxwhwU1oKqy7PXdmGteRxJwqKFBJS46PPtQCrVijjrXn5iqvC5nodL+gQ5Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T03:21:05.453966Z","signed_message":"canonical_sha256_bytes"},"source_id":"2005.12515","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ec1229af23fa73d8282e40426a8417e88b4a62efb6c946e66c2d0ce938744049","sha256:2b40f3095d8d82cee42320bf30529a013f5812b5b529de5920c42b5c2315ac58"],"state_sha256":"3a879d2be8aa6eff712cefa09b4cfd316ad27a73dc202d4fb8656e5decab77dd"}