{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:J4RZPWEGTCM67XQLXCNHIH6TYO","short_pith_number":"pith:J4RZPWEG","schema_version":"1.0","canonical_sha256":"4f2397d8869899efde0bb89a741fd3c3aeab9ad48f9c1f2b099533cc5f76e1f9","source":{"kind":"arxiv","id":"2606.01252","version":1},"attestation_state":"computed","paper":{"title":"Understanding LLM Behavior in Multi-Target Cross-Lingual Summarization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Gary Geunbae Lee, Hinrich Schuetze, Jungseul Ok, Mingyang Wang, Sangwon Ryu, Yihong Liu, Yunsu Kim","submitted_at":"2026-05-31T14:12:58Z","abstract_excerpt":"Multi-target cross-lingual text summarization (MTXLS), which summarizes a source document into multiple target languages, is increasingly important as users consume content in diverse languages, but remains underexplored. To address this gap, we introduce multi-target cross-lingual element-aware (MEA), a new MTXLS benchmark covering 24 target languages. We benchmark end-to-end and pipeline approaches across various LLMs and show that MTXLS performance still substantially lags behind English monolingual summarization. To better understand MTXLS in LLMs, we propose a layer-wise analysis framewor"},"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":"2606.01252","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-31T14:12:58Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"298f761618727d8cb5b63bd285b44d852d547de16d1c8440fc47d4caad65b32c","abstract_canon_sha256":"01628c11fe62ff5dd3151099981ca2b6dc9e3cef07884901f7fb5b357329e90d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T02:04:28.019033Z","signature_b64":"S4FHDIFAxQj/sxfod5oBrhntGtAfAQ9/LIMXZOROwokkBV5YgNnxIBguFJcjNIIhbnE/GWs/Cbml+yFL08aWCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4f2397d8869899efde0bb89a741fd3c3aeab9ad48f9c1f2b099533cc5f76e1f9","last_reissued_at":"2026-06-02T02:04:28.018634Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T02:04:28.018634Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Understanding LLM Behavior in Multi-Target Cross-Lingual Summarization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Gary Geunbae Lee, Hinrich Schuetze, Jungseul Ok, Mingyang Wang, Sangwon Ryu, Yihong Liu, Yunsu Kim","submitted_at":"2026-05-31T14:12:58Z","abstract_excerpt":"Multi-target cross-lingual text summarization (MTXLS), which summarizes a source document into multiple target languages, is increasingly important as users consume content in diverse languages, but remains underexplored. To address this gap, we introduce multi-target cross-lingual element-aware (MEA), a new MTXLS benchmark covering 24 target languages. We benchmark end-to-end and pipeline approaches across various LLMs and show that MTXLS performance still substantially lags behind English monolingual summarization. To better understand MTXLS in LLMs, we propose a layer-wise analysis framewor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.01252","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/2606.01252/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":"2606.01252","created_at":"2026-06-02T02:04:28.018693+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.01252v1","created_at":"2026-06-02T02:04:28.018693+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.01252","created_at":"2026-06-02T02:04:28.018693+00:00"},{"alias_kind":"pith_short_12","alias_value":"J4RZPWEGTCM6","created_at":"2026-06-02T02:04:28.018693+00:00"},{"alias_kind":"pith_short_16","alias_value":"J4RZPWEGTCM67XQL","created_at":"2026-06-02T02:04:28.018693+00:00"},{"alias_kind":"pith_short_8","alias_value":"J4RZPWEG","created_at":"2026-06-02T02:04:28.018693+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/J4RZPWEGTCM67XQLXCNHIH6TYO","json":"https://pith.science/pith/J4RZPWEGTCM67XQLXCNHIH6TYO.json","graph_json":"https://pith.science/api/pith-number/J4RZPWEGTCM67XQLXCNHIH6TYO/graph.json","events_json":"https://pith.science/api/pith-number/J4RZPWEGTCM67XQLXCNHIH6TYO/events.json","paper":"https://pith.science/paper/J4RZPWEG"},"agent_actions":{"view_html":"https://pith.science/pith/J4RZPWEGTCM67XQLXCNHIH6TYO","download_json":"https://pith.science/pith/J4RZPWEGTCM67XQLXCNHIH6TYO.json","view_paper":"https://pith.science/paper/J4RZPWEG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.01252&json=true","fetch_graph":"https://pith.science/api/pith-number/J4RZPWEGTCM67XQLXCNHIH6TYO/graph.json","fetch_events":"https://pith.science/api/pith-number/J4RZPWEGTCM67XQLXCNHIH6TYO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/J4RZPWEGTCM67XQLXCNHIH6TYO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/J4RZPWEGTCM67XQLXCNHIH6TYO/action/storage_attestation","attest_author":"https://pith.science/pith/J4RZPWEGTCM67XQLXCNHIH6TYO/action/author_attestation","sign_citation":"https://pith.science/pith/J4RZPWEGTCM67XQLXCNHIH6TYO/action/citation_signature","submit_replication":"https://pith.science/pith/J4RZPWEGTCM67XQLXCNHIH6TYO/action/replication_record"}},"created_at":"2026-06-02T02:04:28.018693+00:00","updated_at":"2026-06-02T02:04:28.018693+00:00"}