{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:FQGHVF23AA6GRXPBZMLBSDXVA3","short_pith_number":"pith:FQGHVF23","canonical_record":{"source":{"id":"2504.14690","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CL","submitted_at":"2025-04-20T17:43:47Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"46bebda056e4de51d5caeffca3424d943785192c282b80e233cf01e6b4412dfb","abstract_canon_sha256":"68424e11e87cd9fa4cce361d19c668a3b1ba02e8d28a04443f68f824408a6d67"},"schema_version":"1.0"},"canonical_sha256":"2c0c7a975b003c68dde1cb16190ef506e741dabf2973588602864ab1d63e53b0","source":{"kind":"arxiv","id":"2504.14690","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.14690","created_at":"2026-07-05T10:51:49Z"},{"alias_kind":"arxiv_version","alias_value":"2504.14690v1","created_at":"2026-07-05T10:51:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.14690","created_at":"2026-07-05T10:51:49Z"},{"alias_kind":"pith_short_12","alias_value":"FQGHVF23AA6G","created_at":"2026-07-05T10:51:49Z"},{"alias_kind":"pith_short_16","alias_value":"FQGHVF23AA6GRXPB","created_at":"2026-07-05T10:51:49Z"},{"alias_kind":"pith_short_8","alias_value":"FQGHVF23","created_at":"2026-07-05T10:51:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:FQGHVF23AA6GRXPBZMLBSDXVA3","target":"record","payload":{"canonical_record":{"source":{"id":"2504.14690","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CL","submitted_at":"2025-04-20T17:43:47Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"46bebda056e4de51d5caeffca3424d943785192c282b80e233cf01e6b4412dfb","abstract_canon_sha256":"68424e11e87cd9fa4cce361d19c668a3b1ba02e8d28a04443f68f824408a6d67"},"schema_version":"1.0"},"canonical_sha256":"2c0c7a975b003c68dde1cb16190ef506e741dabf2973588602864ab1d63e53b0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:51:49.112957Z","signature_b64":"+EAJUPHsh6jojjQHheFcQ1rLv4pnYq4Vuag4mUk3ZUQbbtFRQ+eCpBz5zVfHrp41/dZNXhzqnOiOCGRiIj0XBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2c0c7a975b003c68dde1cb16190ef506e741dabf2973588602864ab1d63e53b0","last_reissued_at":"2026-07-05T10:51:49.112442Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:51:49.112442Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.14690","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:51:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k9o6YOZx/yiU9mNUAKGq9deOV7/3Pup9LDyfQFcOnFA7TjIB1qfIzTzmclYyxryei16yLE8BT11lXoMQriSlDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T08:37:23.004438Z"},"content_sha256":"04bd9738d9270491352c8bf7262a8581b4d80a0fd8d98b59f878f8045d42b783","schema_version":"1.0","event_id":"sha256:04bd9738d9270491352c8bf7262a8581b4d80a0fd8d98b59f878f8045d42b783"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:FQGHVF23AA6GRXPBZMLBSDXVA3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FarsEval-PKBETS: A new diverse benchmark for evaluating Persian large language models","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Amir Mohseni, Maryam Azimi, Mehrnoush Shamsfard, Mohammad Mahdi Chizari, Morteza Mahdavi Mortazavi, Mostafa Karimi manesh, Mostafa Masumi, Motahareh Ramezani, Niki Pourazin, Sahar Maleki, Sama Khoraminejad, Sarina Chitsaz, Sayed Ali Musavi Khoeini, Seyed Mohammad Hossein Hashemi, Seyed Soroush Majd, Sogol Alipour, Tara Zare, Zahra Saaberi, Zahra Vatankhah","submitted_at":"2025-04-20T17:43:47Z","abstract_excerpt":"Research on evaluating and analyzing large language models (LLMs) has been extensive for resource-rich languages such as English, yet their performance in languages such as Persian has received considerably less attention. This paper introduces FarsEval-PKBETS benchmark, a subset of FarsEval project for evaluating large language models in Persian. This benchmark consists of 4000 questions and answers in various formats, including multiple choice, short answer and descriptive responses. It covers a wide range of domains and tasks,including medicine, law, religion, Persian language, encyclopedic"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.14690","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/2504.14690/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:51:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CoCQetyfka6bivMDWG01M7dM/gwq1KIF5fqp0VgkXEjvOYuNztN+EqdoIP8kBtiHu3YKynDTN2Q/iXoH/505Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T08:37:23.004998Z"},"content_sha256":"546b75a2376229998cc7fb20dea5a809b094952aed828da7eadd23eddbd98e0e","schema_version":"1.0","event_id":"sha256:546b75a2376229998cc7fb20dea5a809b094952aed828da7eadd23eddbd98e0e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FQGHVF23AA6GRXPBZMLBSDXVA3/bundle.json","state_url":"https://pith.science/pith/FQGHVF23AA6GRXPBZMLBSDXVA3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FQGHVF23AA6GRXPBZMLBSDXVA3/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-18T08:37:23Z","links":{"resolver":"https://pith.science/pith/FQGHVF23AA6GRXPBZMLBSDXVA3","bundle":"https://pith.science/pith/FQGHVF23AA6GRXPBZMLBSDXVA3/bundle.json","state":"https://pith.science/pith/FQGHVF23AA6GRXPBZMLBSDXVA3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FQGHVF23AA6GRXPBZMLBSDXVA3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:FQGHVF23AA6GRXPBZMLBSDXVA3","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":"68424e11e87cd9fa4cce361d19c668a3b1ba02e8d28a04443f68f824408a6d67","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CL","submitted_at":"2025-04-20T17:43:47Z","title_canon_sha256":"46bebda056e4de51d5caeffca3424d943785192c282b80e233cf01e6b4412dfb"},"schema_version":"1.0","source":{"id":"2504.14690","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.14690","created_at":"2026-07-05T10:51:49Z"},{"alias_kind":"arxiv_version","alias_value":"2504.14690v1","created_at":"2026-07-05T10:51:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.14690","created_at":"2026-07-05T10:51:49Z"},{"alias_kind":"pith_short_12","alias_value":"FQGHVF23AA6G","created_at":"2026-07-05T10:51:49Z"},{"alias_kind":"pith_short_16","alias_value":"FQGHVF23AA6GRXPB","created_at":"2026-07-05T10:51:49Z"},{"alias_kind":"pith_short_8","alias_value":"FQGHVF23","created_at":"2026-07-05T10:51:49Z"}],"graph_snapshots":[{"event_id":"sha256:546b75a2376229998cc7fb20dea5a809b094952aed828da7eadd23eddbd98e0e","target":"graph","created_at":"2026-07-05T10:51:49Z","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/2504.14690/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Research on evaluating and analyzing large language models (LLMs) has been extensive for resource-rich languages such as English, yet their performance in languages such as Persian has received considerably less attention. This paper introduces FarsEval-PKBETS benchmark, a subset of FarsEval project for evaluating large language models in Persian. This benchmark consists of 4000 questions and answers in various formats, including multiple choice, short answer and descriptive responses. It covers a wide range of domains and tasks,including medicine, law, religion, Persian language, encyclopedic","authors_text":"Amir Mohseni, Maryam Azimi, Mehrnoush Shamsfard, Mohammad Mahdi Chizari, Morteza Mahdavi Mortazavi, Mostafa Karimi manesh, Mostafa Masumi, Motahareh Ramezani, Niki Pourazin, Sahar Maleki, Sama Khoraminejad, Sarina Chitsaz, Sayed Ali Musavi Khoeini, Seyed Mohammad Hossein Hashemi, Seyed Soroush Majd, Sogol Alipour, Tara Zare, Zahra Saaberi, Zahra Vatankhah","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CL","submitted_at":"2025-04-20T17:43:47Z","title":"FarsEval-PKBETS: A new diverse benchmark for evaluating Persian large language models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.14690","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":"sha256:04bd9738d9270491352c8bf7262a8581b4d80a0fd8d98b59f878f8045d42b783","target":"record","created_at":"2026-07-05T10:51:49Z","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":"68424e11e87cd9fa4cce361d19c668a3b1ba02e8d28a04443f68f824408a6d67","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CL","submitted_at":"2025-04-20T17:43:47Z","title_canon_sha256":"46bebda056e4de51d5caeffca3424d943785192c282b80e233cf01e6b4412dfb"},"schema_version":"1.0","source":{"id":"2504.14690","kind":"arxiv","version":1}},"canonical_sha256":"2c0c7a975b003c68dde1cb16190ef506e741dabf2973588602864ab1d63e53b0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2c0c7a975b003c68dde1cb16190ef506e741dabf2973588602864ab1d63e53b0","first_computed_at":"2026-07-05T10:51:49.112442Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:51:49.112442Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+EAJUPHsh6jojjQHheFcQ1rLv4pnYq4Vuag4mUk3ZUQbbtFRQ+eCpBz5zVfHrp41/dZNXhzqnOiOCGRiIj0XBA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:51:49.112957Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.14690","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:04bd9738d9270491352c8bf7262a8581b4d80a0fd8d98b59f878f8045d42b783","sha256:546b75a2376229998cc7fb20dea5a809b094952aed828da7eadd23eddbd98e0e"],"state_sha256":"7b4eac548aa8a766c9d8783ab7451ea4413788db24b18443494c761548131977"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e0ryINzpUNOQ93KhzUMVykTPIRn3SMIT5YI6B40/2pEwUIdiE2xSSQrfaeii3ZkTa2CYHa5GuJWcRiXXA7q8Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T08:37:23.012789Z","bundle_sha256":"8bcf364e68440f201a9810b2d84325ed62f3a90d5b1b4eb6c52fb387e27fd716"}}