{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:L2UBU3SUD5SNDCDNCA6ONAYDM3","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":"e903595fb18f19ad0030fa9b9ad91f788034faa80a97aa8aa985e6e9d38135df","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-17T14:25:24Z","title_canon_sha256":"355027bc864ec21fd0646056007d5141edb0525ff2e5dabcbfae1d42d38730d7"},"schema_version":"1.0","source":{"id":"2507.14239","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.14239","created_at":"2026-07-05T11:40:02Z"},{"alias_kind":"arxiv_version","alias_value":"2507.14239v1","created_at":"2026-07-05T11:40:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.14239","created_at":"2026-07-05T11:40:02Z"},{"alias_kind":"pith_short_12","alias_value":"L2UBU3SUD5SN","created_at":"2026-07-05T11:40:02Z"},{"alias_kind":"pith_short_16","alias_value":"L2UBU3SUD5SNDCDN","created_at":"2026-07-05T11:40:02Z"},{"alias_kind":"pith_short_8","alias_value":"L2UBU3SU","created_at":"2026-07-05T11:40:02Z"}],"graph_snapshots":[{"event_id":"sha256:e3f6ab39e5d95feaa02ac9d9d008c886a9c637040dbba9a4134e80eeb65501b0","target":"graph","created_at":"2026-07-05T11:40:02Z","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/2507.14239/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multilingual Large Language Models(MLLMs) demonstrate strong generalization across languages, yet they remain prone to hallucinations, especially in low-resource languages, due to training data imbalances. These hallucinations, which include inaccurate or fabricated outputs, are particularly problematic in domain-specific generation tasks (Chataigner et al., 2024). To address this challenge, we propose CCL-XCoT(Curriculum-based Contrastive Learning-based Cross-lingual Chain-of-Thought), a two-stage fine-tuning framework for mitigating hallucination in MLLMs. Our approach first enhances cross-l","authors_text":"Aiti Aw, Bowei Zou, Kui Wu, Roy Ka-Wei Lee, Weihua Zheng, Zhengyuan Liu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-17T14:25:24Z","title":"CCL-XCoT: An Efficient Cross-Lingual Knowledge Transfer Method for Mitigating Hallucination Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.14239","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":"sha256:7d680e2ba8262abadefa5446da513cf1b3c8a07e2fca85cad5005ed8623dbf0b","target":"record","created_at":"2026-07-05T11:40:02Z","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":"e903595fb18f19ad0030fa9b9ad91f788034faa80a97aa8aa985e6e9d38135df","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-17T14:25:24Z","title_canon_sha256":"355027bc864ec21fd0646056007d5141edb0525ff2e5dabcbfae1d42d38730d7"},"schema_version":"1.0","source":{"id":"2507.14239","kind":"arxiv","version":1}},"canonical_sha256":"5ea81a6e541f64d1886d103ce6830366dca1e5f7e1a80dfe491341fc2ce70793","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5ea81a6e541f64d1886d103ce6830366dca1e5f7e1a80dfe491341fc2ce70793","first_computed_at":"2026-07-05T11:40:02.613269Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:40:02.613269Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Sh/6jCgtuVpBZsePjaDndosOpv7MJVY1/G/p7ycCNcZ7jd7wYHNYu8yJZMe5Nxh/2++tQTgG07tkj0gNMUvhDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:40:02.613773Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.14239","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7d680e2ba8262abadefa5446da513cf1b3c8a07e2fca85cad5005ed8623dbf0b","sha256:e3f6ab39e5d95feaa02ac9d9d008c886a9c637040dbba9a4134e80eeb65501b0"],"state_sha256":"464440e42d3159cc7ca1bcb6cb5e93f321206d8c9520be39c1e8d56e5595a086"}