{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:YE77F4GQRY7UITH6ZJYYHDZKVL","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":"33acbe227ada2f7a0c82cdac4e102aede266ffc7beee93bfb09ac172c26d8adf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-04-28T20:03:46Z","title_canon_sha256":"4f9af21f2b07cdc85d9e77553479625eab9e264a4dcfcac78270f1a4539fca8d"},"schema_version":"1.0","source":{"id":"2305.00076","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.00076","created_at":"2026-07-05T06:05:37Z"},{"alias_kind":"arxiv_version","alias_value":"2305.00076v1","created_at":"2026-07-05T06:05:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.00076","created_at":"2026-07-05T06:05:37Z"},{"alias_kind":"pith_short_12","alias_value":"YE77F4GQRY7U","created_at":"2026-07-05T06:05:37Z"},{"alias_kind":"pith_short_16","alias_value":"YE77F4GQRY7UITH6","created_at":"2026-07-05T06:05:37Z"},{"alias_kind":"pith_short_8","alias_value":"YE77F4GQ","created_at":"2026-07-05T06:05:37Z"}],"graph_snapshots":[{"event_id":"sha256:1890763f23e160bab4e7c6d23365ee542c1ae454f87ba0c7ec68e3062134c1b8","target":"graph","created_at":"2026-07-05T06:05:37Z","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/2305.00076/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present the findings of our participation in the SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS) task, a shared task on offensive language (sexism) detection on English Gab and Reddit dataset. We investigated the effects of transferring two language models: XLM-T (sentiment classification) and HateBERT (same domain -- Reddit) for multi-level classification into Sexist or not Sexist, and other subsequent sub-classifications of the sexist data. We also use synthetic classification of unlabelled dataset and intermediary class information to maximize the performance of our m","authors_text":"Aliyu Yusuf, Falalu Ibrahim Lawan, Ibrahim Said Ahmad, Idris Abdulmumin, Saheed Abdullahi Salahudeen, Saminu Mohammad Aliyu, Shamsuddeen Hassan Muhammad","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-04-28T20:03:46Z","title":"HausaNLP at SemEval-2023 Task 10: Transfer Learning, Synthetic Data and Side-Information for Multi-Level Sexism Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.00076","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:b43c8c5467c778ad87a98a6aa9e5b438f51720548d4ad34edb1456fbfa321660","target":"record","created_at":"2026-07-05T06:05:37Z","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":"33acbe227ada2f7a0c82cdac4e102aede266ffc7beee93bfb09ac172c26d8adf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-04-28T20:03:46Z","title_canon_sha256":"4f9af21f2b07cdc85d9e77553479625eab9e264a4dcfcac78270f1a4539fca8d"},"schema_version":"1.0","source":{"id":"2305.00076","kind":"arxiv","version":1}},"canonical_sha256":"c13ff2f0d08e3f444cfeca71838f2aaae7f360e5f8e24f6ddc8289f22c26d287","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c13ff2f0d08e3f444cfeca71838f2aaae7f360e5f8e24f6ddc8289f22c26d287","first_computed_at":"2026-07-05T06:05:37.135971Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:05:37.135971Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ovAYyUbdvfMre1gWnD3UZbU+qzDneC9JArCeLJ2L9ZvyIs3AJP1LvqMZZjn09hsrRD96eUpTQEDWvHAuaVCxAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:05:37.136546Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.00076","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b43c8c5467c778ad87a98a6aa9e5b438f51720548d4ad34edb1456fbfa321660","sha256:1890763f23e160bab4e7c6d23365ee542c1ae454f87ba0c7ec68e3062134c1b8"],"state_sha256":"228ce31476d1fc1dbd2b95fac520cc7e2a903eb9228aba03f9ee1c0f8a5603af"}