{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:3BFCPCOZDS3SVHULV6Y5ZWJQVT","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":"3f1acd9194fbbcbe014768ee0d425c3db4b7558a3edbcca0c708dda75d603e1e","cross_cats_sorted":["cs.AI","cs.CY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-04T09:11:24Z","title_canon_sha256":"c6566e92f5893eeb5a2bded7f55cc7a793d4f1e558439fb7b8b6c3f20da920d8"},"schema_version":"1.0","source":{"id":"1904.02418","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.02418","created_at":"2026-05-17T23:49:23Z"},{"alias_kind":"arxiv_version","alias_value":"1904.02418v1","created_at":"2026-05-17T23:49:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.02418","created_at":"2026-05-17T23:49:23Z"},{"alias_kind":"pith_short_12","alias_value":"3BFCPCOZDS3S","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"3BFCPCOZDS3SVHUL","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"3BFCPCOZ","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:2b55bc69a986c3282a7cb0519495bd48dba5b8f1cb38c8b24aca6ed9c792f1a7","target":"graph","created_at":"2026-05-17T23:49:23Z","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"},"paper":{"abstract_excerpt":"Existing computational models to understand hate speech typically frame the problem as a simple classification task, bypassing the understanding of hate symbols (e.g., 14 words, kigy) and their secret connotations. In this paper, we propose a novel task of deciphering hate symbols. To do this, we leverage the Urban Dictionary and collected a new, symbol-rich Twitter corpus of hate speech. We investigate neural network latent context models for deciphering hate symbols. More specifically, we study Sequence-to-Sequence models and show how they are able to crack the ciphers based on context. Furt","authors_text":"Elizabeth Belding, Jing Qian, Mai ElSherief, William Yang Wang","cross_cats":["cs.AI","cs.CY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-04T09:11:24Z","title":"Learning to Decipher Hate Symbols"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.02418","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":"sha256:7fb93244d947543110c7348b67692d4dcad5ebb84aa7401ca33e00feac29f836","target":"record","created_at":"2026-05-17T23:49:23Z","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":"3f1acd9194fbbcbe014768ee0d425c3db4b7558a3edbcca0c708dda75d603e1e","cross_cats_sorted":["cs.AI","cs.CY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-04T09:11:24Z","title_canon_sha256":"c6566e92f5893eeb5a2bded7f55cc7a793d4f1e558439fb7b8b6c3f20da920d8"},"schema_version":"1.0","source":{"id":"1904.02418","kind":"arxiv","version":1}},"canonical_sha256":"d84a2789d91cb72a9e8bafb1dcd930acf0e76f6da0836f3282fc1be1c719bfc5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d84a2789d91cb72a9e8bafb1dcd930acf0e76f6da0836f3282fc1be1c719bfc5","first_computed_at":"2026-05-17T23:49:23.734926Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:49:23.734926Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9QjuNC9JpcLfXdGqTuIJgON0m00c6rhJyfCfa7zQhtNr7uGMqO60va6kl0ba8k0gF1gQ2uncgamVYjltDFWnCw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:49:23.735518Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.02418","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7fb93244d947543110c7348b67692d4dcad5ebb84aa7401ca33e00feac29f836","sha256:2b55bc69a986c3282a7cb0519495bd48dba5b8f1cb38c8b24aca6ed9c792f1a7"],"state_sha256":"59419a860204d090e30bfb965b96a89b1e77946a1b660dabbb50f455573f62c1"}