{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:UBJG3IEZH3O3S53SKQCX7OZ7CZ","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":"5a9aaa03f9250081e7296e1ce82078842a6314672a753990ab4f61ed38eb4dcb","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-10-09T13:53:06Z","title_canon_sha256":"584fd630c35e002ff787429d1b27669ceb433c8ed0c63317455ea8c33b797067"},"schema_version":"1.0","source":{"id":"2210.04267","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.04267","created_at":"2026-07-05T05:23:59Z"},{"alias_kind":"arxiv_version","alias_value":"2210.04267v3","created_at":"2026-07-05T05:23:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.04267","created_at":"2026-07-05T05:23:59Z"},{"alias_kind":"pith_short_12","alias_value":"UBJG3IEZH3O3","created_at":"2026-07-05T05:23:59Z"},{"alias_kind":"pith_short_16","alias_value":"UBJG3IEZH3O3S53S","created_at":"2026-07-05T05:23:59Z"},{"alias_kind":"pith_short_8","alias_value":"UBJG3IEZ","created_at":"2026-07-05T05:23:59Z"}],"graph_snapshots":[{"event_id":"sha256:261df74793187da1a44d28536786a7d8b007260ac8369cb008aea6d499aeb0b7","target":"graph","created_at":"2026-07-05T05:23:59Z","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/2210.04267/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Pre-training large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. Although this method has proven to be effective for many domains, it might not always provide desirable benefits. In this paper, we study the effects of hateful pre-training on low-resource hate speech classification tasks. While previous studies on the English language have emphasized its importance, we aim to augment their observations with some non-obvious insights. We evaluate different variations of tweet-based BERT models pre-trained on hateful, non-hatefu","authors_text":"Aditya Kane, Omkar Gokhale, Raviraj Joshi, Shantanu Patankar, Tanmay Chavan","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-10-09T13:53:06Z","title":"Spread Love Not Hate: Undermining the Importance of Hateful Pre-training for Hate Speech Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.04267","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:eb2d3264b7f75a4d2f8b55dfa3521868b4f888e115fb6d28e727db7f941f1b0c","target":"record","created_at":"2026-07-05T05:23:59Z","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":"5a9aaa03f9250081e7296e1ce82078842a6314672a753990ab4f61ed38eb4dcb","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-10-09T13:53:06Z","title_canon_sha256":"584fd630c35e002ff787429d1b27669ceb433c8ed0c63317455ea8c33b797067"},"schema_version":"1.0","source":{"id":"2210.04267","kind":"arxiv","version":3}},"canonical_sha256":"a0526da0993eddb9777254057fbb3f165914d77ca4b5b5e3cf93273fb249ac9e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a0526da0993eddb9777254057fbb3f165914d77ca4b5b5e3cf93273fb249ac9e","first_computed_at":"2026-07-05T05:23:59.145065Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:23:59.145065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DLd6eYI/oOnUDTVgRdC9CSL/LFaYj/WjksxxI2oi3tm9kC5beZMl4Q63wS5yRkr9V/D5J98/aTt6HqRaAiyiDw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:23:59.145481Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.04267","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eb2d3264b7f75a4d2f8b55dfa3521868b4f888e115fb6d28e727db7f941f1b0c","sha256:261df74793187da1a44d28536786a7d8b007260ac8369cb008aea6d499aeb0b7"],"state_sha256":"4a28e46c0773d98d15fd0adc7519a436b4ed117e5468ddfecc2100da351aa9c6"}