{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SVKSCKYYAF2ZMIOR3DFK3E6U7J","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":"5fedf69e2590bb1cd3ac44e47079d7c5c9c60f55e0c1b72ce94b80000a618544","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-11-17T09:43:54Z","title_canon_sha256":"e4ab23d75a45cde41ae20f22404a35cb940777b5d06b92332a20c18b2bc1b8d4"},"schema_version":"1.0","source":{"id":"2511.13182","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2511.13182","created_at":"2026-07-14T01:22:02Z"},{"alias_kind":"arxiv_version","alias_value":"2511.13182v3","created_at":"2026-07-14T01:22:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.13182","created_at":"2026-07-14T01:22:02Z"},{"alias_kind":"pith_short_12","alias_value":"SVKSCKYYAF2Z","created_at":"2026-07-14T01:22:02Z"},{"alias_kind":"pith_short_16","alias_value":"SVKSCKYYAF2ZMIOR","created_at":"2026-07-14T01:22:02Z"},{"alias_kind":"pith_short_8","alias_value":"SVKSCKYY","created_at":"2026-07-14T01:22:02Z"}],"graph_snapshots":[{"event_id":"sha256:98a831edb29a8b837927befe31f58655cad74838140f5250ff7eba354da573c6","target":"graph","created_at":"2026-07-14T01:22:02Z","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/2511.13182/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automatic diacritic restoration is crucial for text processing in languages with rich diacritical marks, such as Romanian. This study evaluates the performance of several large language models (LLMs) in restoring diacritics in Romanian texts. Using a comprehensive corpus, we tested models including OpenAI's GPT-3.5, GPT-4, GPT-4o, Google's Gemini 1.0 Pro, Meta's Llama 2 and Llama 3, MistralAI's Mixtral 8x7B Instruct, airoboros 70B, and OpenLLM-Ro's RoLlama 2 7B, under multiple prompt templates ranging from zero-shot to complex multi-shot instructions. Results show that models such as GPT-4o ac","authors_text":"Laura Diosan, Mihai Nadas","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-11-17T09:43:54Z","title":"Evaluating Large Language Models for Diacritic Restoration in Romanian Texts: A Comparative Study"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.13182","kind":"arxiv","version":3},"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":"sha256:32ab9b373ab487bfbdcfd59045244b66a4f1f9bbfaaaca92055f6b8a77738c10","target":"record","created_at":"2026-07-14T01:22:02Z","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":"5fedf69e2590bb1cd3ac44e47079d7c5c9c60f55e0c1b72ce94b80000a618544","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-11-17T09:43:54Z","title_canon_sha256":"e4ab23d75a45cde41ae20f22404a35cb940777b5d06b92332a20c18b2bc1b8d4"},"schema_version":"1.0","source":{"id":"2511.13182","kind":"arxiv","version":3}},"canonical_sha256":"9555212b1801759621d1d8caad93d4fa6403f6afd128785374382048796d2944","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9555212b1801759621d1d8caad93d4fa6403f6afd128785374382048796d2944","first_computed_at":"2026-07-14T01:22:02.234562Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-14T01:22:02.234562Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6SoJornFNOx9y+Z45eQ0XyLio8Art6ST+I7hlQhD4Rjuql0LrzBf01thUu7FZEE9Zpc4btWLTlhwiR+8kl5kDA==","signature_status":"signed_v1","signed_at":"2026-07-14T01:22:02.235499Z","signed_message":"canonical_sha256_bytes"},"source_id":"2511.13182","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:32ab9b373ab487bfbdcfd59045244b66a4f1f9bbfaaaca92055f6b8a77738c10","sha256:98a831edb29a8b837927befe31f58655cad74838140f5250ff7eba354da573c6"],"state_sha256":"333c80c91c8904779c3dd86e82317e81eab92d2a86e189eb9628c12c38406f59"}