{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:6CA6C3474GDJBXXF67UVHFHM2D","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":"b433032afd09d5387007e90063573a486d223b76dc9cecf843a956c0b29caf03","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-23T02:21:24Z","title_canon_sha256":"314944d4d32f078ca7dca91b9ac0cf9ad0580841383c8da8f9435055014f27b0"},"schema_version":"1.0","source":{"id":"2402.15059","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.15059","created_at":"2026-07-05T07:48:21Z"},{"alias_kind":"arxiv_version","alias_value":"2402.15059v1","created_at":"2026-07-05T07:48:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.15059","created_at":"2026-07-05T07:48:21Z"},{"alias_kind":"pith_short_12","alias_value":"6CA6C3474GDJ","created_at":"2026-07-05T07:48:21Z"},{"alias_kind":"pith_short_16","alias_value":"6CA6C3474GDJBXXF","created_at":"2026-07-05T07:48:21Z"},{"alias_kind":"pith_short_8","alias_value":"6CA6C347","created_at":"2026-07-05T07:48:21Z"}],"graph_snapshots":[{"event_id":"sha256:0b952fc43565ded6e0f484752fb79b21af6d89f79dd5024f1e9441f77d055cdd","target":"graph","created_at":"2026-07-05T07:48:21Z","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/2402.15059/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"State-of-the-art neural retrievers predominantly focus on high-resource languages like English, which impedes their adoption in retrieval scenarios involving other languages. Current approaches circumvent the lack of high-quality labeled data in non-English languages by leveraging multilingual pretrained language models capable of cross-lingual transfer. However, these models require substantial task-specific fine-tuning across multiple languages, often perform poorly in languages with minimal representation in the pretraining corpus, and struggle to incorporate new languages after the pretrai","authors_text":"Antoine Louis, Gerasimos Spanakis, Gijs van Dijck, Vageesh Saxena","cross_cats":["cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-23T02:21:24Z","title":"ColBERT-XM: A Modular Multi-Vector Representation Model for Zero-Shot Multilingual Information Retrieval"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.15059","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:e8a686980e6149bcc712121dd94dedb4513bda63e920d1616e4eb6012dc8482a","target":"record","created_at":"2026-07-05T07:48:21Z","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":"b433032afd09d5387007e90063573a486d223b76dc9cecf843a956c0b29caf03","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-23T02:21:24Z","title_canon_sha256":"314944d4d32f078ca7dca91b9ac0cf9ad0580841383c8da8f9435055014f27b0"},"schema_version":"1.0","source":{"id":"2402.15059","kind":"arxiv","version":1}},"canonical_sha256":"f081e16f9fe18690dee5f7e95394ecd0dfea85e9a1e6683f42e257eb62155d9d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f081e16f9fe18690dee5f7e95394ecd0dfea85e9a1e6683f42e257eb62155d9d","first_computed_at":"2026-07-05T07:48:21.392955Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:48:21.392955Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wWumn65g60qgmz02eCK5Yc1eEuf1e/cbhsyD+iQvx4prjLC8hlBJgLo1opLFnVED//m88tpBA/AdOc1AqDh/BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:48:21.393494Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.15059","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e8a686980e6149bcc712121dd94dedb4513bda63e920d1616e4eb6012dc8482a","sha256:0b952fc43565ded6e0f484752fb79b21af6d89f79dd5024f1e9441f77d055cdd"],"state_sha256":"a487cb67e848f7e1699d50f07f807e2db0bd8cab976a8977b27f74ab95252f93"}