{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:RBTNXLFFKNCIIULE2LHWA5G2XW","short_pith_number":"pith:RBTNXLFF","schema_version":"1.0","canonical_sha256":"8866dbaca55344845164d2cf6074dabd8a469f79b0eecec4080fa1058357d456","source":{"kind":"arxiv","id":"2206.01583","version":1},"attestation_state":"computed","paper":{"title":"Findings of the The RuATD Shared Task 2022 on Artificial Text Detection in Russian","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Alena Fenogenova, Anastasiya Valeeva, Daniil Chernianskii, Ekaterina Artemova, Elena Tutubalina, Ivan Smurov, Marat Saidov, Tatiana Shamardina, Tatiana Shavrina, Vladislav Mikhailov","submitted_at":"2022-06-03T14:12:33Z","abstract_excerpt":"We present the shared task on artificial text detection in Russian, which is organized as a part of the Dialogue Evaluation initiative, held in 2022. The shared task dataset includes texts from 14 text generators, i.e., one human writer and 13 text generative models fine-tuned for one or more of the following generation tasks: machine translation, paraphrase generation, text summarization, text simplification. We also consider back-translation and zero-shot generation approaches. The human-written texts are collected from publicly available resources across multiple domains. The shared task co"},"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":"2206.01583","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-06-03T14:12:33Z","cross_cats_sorted":[],"title_canon_sha256":"816d293ef9636bf5282d82f0c873eef5f927698efd51918ac84b3f09cf2f0903","abstract_canon_sha256":"b2d876f92d696e9dd445caede598dd6caedbda1a755876e244b6c194d423585b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:56:29.219362Z","signature_b64":"PKOhZYhSAUA/eTLtELKjMznqfHmN/T3yCqBr2AKEtaVpEoFtpUxpP6ptkE3s1E5GOwMbjCeZjJwFHHcxZ8NUDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8866dbaca55344845164d2cf6074dabd8a469f79b0eecec4080fa1058357d456","last_reissued_at":"2026-07-05T06:56:29.218869Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:56:29.218869Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Findings of the The RuATD Shared Task 2022 on Artificial Text Detection in Russian","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Alena Fenogenova, Anastasiya Valeeva, Daniil Chernianskii, Ekaterina Artemova, Elena Tutubalina, Ivan Smurov, Marat Saidov, Tatiana Shamardina, Tatiana Shavrina, Vladislav Mikhailov","submitted_at":"2022-06-03T14:12:33Z","abstract_excerpt":"We present the shared task on artificial text detection in Russian, which is organized as a part of the Dialogue Evaluation initiative, held in 2022. The shared task dataset includes texts from 14 text generators, i.e., one human writer and 13 text generative models fine-tuned for one or more of the following generation tasks: machine translation, paraphrase generation, text summarization, text simplification. We also consider back-translation and zero-shot generation approaches. The human-written texts are collected from publicly available resources across multiple domains. The shared task co"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.01583","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/2206.01583/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":"2206.01583","created_at":"2026-07-05T06:56:29.218925+00:00"},{"alias_kind":"arxiv_version","alias_value":"2206.01583v1","created_at":"2026-07-05T06:56:29.218925+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.01583","created_at":"2026-07-05T06:56:29.218925+00:00"},{"alias_kind":"pith_short_12","alias_value":"RBTNXLFFKNCI","created_at":"2026-07-05T06:56:29.218925+00:00"},{"alias_kind":"pith_short_16","alias_value":"RBTNXLFFKNCIIULE","created_at":"2026-07-05T06:56:29.218925+00:00"},{"alias_kind":"pith_short_8","alias_value":"RBTNXLFF","created_at":"2026-07-05T06:56:29.218925+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2502.11614","citing_title":"Is Human-Like Text Liked by Humans? Multilingual Human Detection and Preference Against AI","ref_index":22,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RBTNXLFFKNCIIULE2LHWA5G2XW","json":"https://pith.science/pith/RBTNXLFFKNCIIULE2LHWA5G2XW.json","graph_json":"https://pith.science/api/pith-number/RBTNXLFFKNCIIULE2LHWA5G2XW/graph.json","events_json":"https://pith.science/api/pith-number/RBTNXLFFKNCIIULE2LHWA5G2XW/events.json","paper":"https://pith.science/paper/RBTNXLFF"},"agent_actions":{"view_html":"https://pith.science/pith/RBTNXLFFKNCIIULE2LHWA5G2XW","download_json":"https://pith.science/pith/RBTNXLFFKNCIIULE2LHWA5G2XW.json","view_paper":"https://pith.science/paper/RBTNXLFF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2206.01583&json=true","fetch_graph":"https://pith.science/api/pith-number/RBTNXLFFKNCIIULE2LHWA5G2XW/graph.json","fetch_events":"https://pith.science/api/pith-number/RBTNXLFFKNCIIULE2LHWA5G2XW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RBTNXLFFKNCIIULE2LHWA5G2XW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RBTNXLFFKNCIIULE2LHWA5G2XW/action/storage_attestation","attest_author":"https://pith.science/pith/RBTNXLFFKNCIIULE2LHWA5G2XW/action/author_attestation","sign_citation":"https://pith.science/pith/RBTNXLFFKNCIIULE2LHWA5G2XW/action/citation_signature","submit_replication":"https://pith.science/pith/RBTNXLFFKNCIIULE2LHWA5G2XW/action/replication_record"}},"created_at":"2026-07-05T06:56:29.218925+00:00","updated_at":"2026-07-05T06:56:29.218925+00:00"}