{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:QHIPMCUNZQX2J7EXITOBZOJZMZ","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":"741f48691a41625c4b70d35e4e9a9965f887068c25146a4e90586d616d83dd1b","cross_cats_sorted":["cs.SI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-03-02T14:02:54Z","title_canon_sha256":"d53f53e3b7490723335efc41b25324afcbff86bcf588e6a109766d01c17860f7"},"schema_version":"1.0","source":{"id":"2203.01111","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.01111","created_at":"2026-07-05T04:37:58Z"},{"alias_kind":"arxiv_version","alias_value":"2203.01111v2","created_at":"2026-07-05T04:37:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.01111","created_at":"2026-07-05T04:37:58Z"},{"alias_kind":"pith_short_12","alias_value":"QHIPMCUNZQX2","created_at":"2026-07-05T04:37:58Z"},{"alias_kind":"pith_short_16","alias_value":"QHIPMCUNZQX2J7EX","created_at":"2026-07-05T04:37:58Z"},{"alias_kind":"pith_short_8","alias_value":"QHIPMCUN","created_at":"2026-07-05T04:37:58Z"}],"graph_snapshots":[{"event_id":"sha256:0c85b4ab429a21dfebd761eafb8570e7942a18f71b93cb6aca8983deca8cbdca","target":"graph","created_at":"2026-07-05T04:37:58Z","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/2203.01111/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The performance of hate speech detection models relies on the datasets on which the models are trained. Existing datasets are mostly prepared with a limited number of instances or hate domains that define hate topics. This hinders large-scale analysis and transfer learning with respect to hate domains. In this study, we construct large-scale tweet datasets for hate speech detection in English and a low-resource language, Turkish, consisting of human-labeled 100k tweets per each. Our datasets are designed to have equal number of tweets distributed over five domains. The experimental results sup","authors_text":"Cagri Toraman, Eyup Halit Yilmaz, Furkan \\c{S}ahinu\\c{c}","cross_cats":["cs.SI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-03-02T14:02:54Z","title":"Large-Scale Hate Speech Detection with Cross-Domain Transfer"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.01111","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":"sha256:2c26b16a349ad12b3e99d46678cb2d1e358b314ece7e3fb7fb2e09511f38c939","target":"record","created_at":"2026-07-05T04:37:58Z","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":"741f48691a41625c4b70d35e4e9a9965f887068c25146a4e90586d616d83dd1b","cross_cats_sorted":["cs.SI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-03-02T14:02:54Z","title_canon_sha256":"d53f53e3b7490723335efc41b25324afcbff86bcf588e6a109766d01c17860f7"},"schema_version":"1.0","source":{"id":"2203.01111","kind":"arxiv","version":2}},"canonical_sha256":"81d0f60a8dcc2fa4fc9744dc1cb9396675bb89ec3afefadef360ed0d5d56c762","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"81d0f60a8dcc2fa4fc9744dc1cb9396675bb89ec3afefadef360ed0d5d56c762","first_computed_at":"2026-07-05T04:37:58.064807Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:37:58.064807Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wVVNoGOG08E03yISSO3yUewaVoFo5t45qfc5IN9CiZcrwSENq/vh+FkPGnj+4gWaUJ0GYJgYyBQXUJY97UIWAw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:37:58.065266Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.01111","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2c26b16a349ad12b3e99d46678cb2d1e358b314ece7e3fb7fb2e09511f38c939","sha256:0c85b4ab429a21dfebd761eafb8570e7942a18f71b93cb6aca8983deca8cbdca"],"state_sha256":"61814f2b2038bba704c9d79a74d414fec5d7d76ab94b1a268206fa7c0878c728"}