{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:2ZWSE3AL4HUY6EPCH2BJXPA4O5","short_pith_number":"pith:2ZWSE3AL","schema_version":"1.0","canonical_sha256":"d66d226c0be1e98f11e23e829bbc1c7745a6d38c4c20def2c88a7037820a8b9d","source":{"kind":"arxiv","id":"2607.02049","version":1},"attestation_state":"computed","paper":{"title":"SPLIT: Cross-Lingual Empathy and Cultural Grounding in English and Ukrainian LLM Responses","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CY"],"primary_cat":"cs.CL","authors_text":"Anna Chorna","submitted_at":"2026-07-02T11:22:01Z","abstract_excerpt":"Large Language Models are increasingly deployed in emotional-support contexts and crisis-related situations. Nevertheless, their cross-lingual abilities in these circumstances remain underexplored. Existing benchmarks emphasize multilingual performance but rarely examine crisis-related empathy and cultural grounding in low-to-mid-resource languages. We introduce SPLIT, a 500-prompt benchmark designed to evaluate LLM consistency in generating emotionally grounded responses across five categories: Stress, Panic, Loneliness, Internal Displacement, and Tension. We evaluate three technically divers"},"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":"2607.02049","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-02T11:22:01Z","cross_cats_sorted":["cs.AI","cs.CY"],"title_canon_sha256":"20154ed5569c5da59bace95df0c00bd08cadf473161300866065276b701faa02","abstract_canon_sha256":"dc8ed17bb80e03567183446c82a77a4f47b7a5644859c3083002e9073e6ba1b6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-03T01:17:38.078818Z","signature_b64":"obgSajd40WeCfxJrdqGNC4zsm7HSlZXRBS16nRLZQ+O9iU46p67YKboY8/J0thNL7lhMiPSXDI8pVmW8FRahDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d66d226c0be1e98f11e23e829bbc1c7745a6d38c4c20def2c88a7037820a8b9d","last_reissued_at":"2026-07-03T01:17:38.078393Z","signature_status":"signed_v1","first_computed_at":"2026-07-03T01:17:38.078393Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SPLIT: Cross-Lingual Empathy and Cultural Grounding in English and Ukrainian LLM Responses","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CY"],"primary_cat":"cs.CL","authors_text":"Anna Chorna","submitted_at":"2026-07-02T11:22:01Z","abstract_excerpt":"Large Language Models are increasingly deployed in emotional-support contexts and crisis-related situations. Nevertheless, their cross-lingual abilities in these circumstances remain underexplored. Existing benchmarks emphasize multilingual performance but rarely examine crisis-related empathy and cultural grounding in low-to-mid-resource languages. We introduce SPLIT, a 500-prompt benchmark designed to evaluate LLM consistency in generating emotionally grounded responses across five categories: Stress, Panic, Loneliness, Internal Displacement, and Tension. We evaluate three technically divers"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.02049","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/2607.02049/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":"2607.02049","created_at":"2026-07-03T01:17:38.078451+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.02049v1","created_at":"2026-07-03T01:17:38.078451+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.02049","created_at":"2026-07-03T01:17:38.078451+00:00"},{"alias_kind":"pith_short_12","alias_value":"2ZWSE3AL4HUY","created_at":"2026-07-03T01:17:38.078451+00:00"},{"alias_kind":"pith_short_16","alias_value":"2ZWSE3AL4HUY6EPC","created_at":"2026-07-03T01:17:38.078451+00:00"},{"alias_kind":"pith_short_8","alias_value":"2ZWSE3AL","created_at":"2026-07-03T01:17:38.078451+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2ZWSE3AL4HUY6EPCH2BJXPA4O5","json":"https://pith.science/pith/2ZWSE3AL4HUY6EPCH2BJXPA4O5.json","graph_json":"https://pith.science/api/pith-number/2ZWSE3AL4HUY6EPCH2BJXPA4O5/graph.json","events_json":"https://pith.science/api/pith-number/2ZWSE3AL4HUY6EPCH2BJXPA4O5/events.json","paper":"https://pith.science/paper/2ZWSE3AL"},"agent_actions":{"view_html":"https://pith.science/pith/2ZWSE3AL4HUY6EPCH2BJXPA4O5","download_json":"https://pith.science/pith/2ZWSE3AL4HUY6EPCH2BJXPA4O5.json","view_paper":"https://pith.science/paper/2ZWSE3AL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.02049&json=true","fetch_graph":"https://pith.science/api/pith-number/2ZWSE3AL4HUY6EPCH2BJXPA4O5/graph.json","fetch_events":"https://pith.science/api/pith-number/2ZWSE3AL4HUY6EPCH2BJXPA4O5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2ZWSE3AL4HUY6EPCH2BJXPA4O5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2ZWSE3AL4HUY6EPCH2BJXPA4O5/action/storage_attestation","attest_author":"https://pith.science/pith/2ZWSE3AL4HUY6EPCH2BJXPA4O5/action/author_attestation","sign_citation":"https://pith.science/pith/2ZWSE3AL4HUY6EPCH2BJXPA4O5/action/citation_signature","submit_replication":"https://pith.science/pith/2ZWSE3AL4HUY6EPCH2BJXPA4O5/action/replication_record"}},"created_at":"2026-07-03T01:17:38.078451+00:00","updated_at":"2026-07-03T01:17:38.078451+00:00"}