{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:5SXMYKCXYJTFEA7WNE4PRUOKQQ","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":"d4d10c716e659b3f27124fe19593ed336c6409aaa642120d4541373a4127a8c1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-02-01T09:41:59Z","title_canon_sha256":"6938d4fdb9a4b5e18fef1243c80f945d6feb2513420f8bc73b6cbe60f3501c76"},"schema_version":"1.0","source":{"id":"2202.00291","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.00291","created_at":"2026-07-05T04:17:20Z"},{"alias_kind":"arxiv_version","alias_value":"2202.00291v2","created_at":"2026-07-05T04:17:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.00291","created_at":"2026-07-05T04:17:20Z"},{"alias_kind":"pith_short_12","alias_value":"5SXMYKCXYJTF","created_at":"2026-07-05T04:17:20Z"},{"alias_kind":"pith_short_16","alias_value":"5SXMYKCXYJTFEA7W","created_at":"2026-07-05T04:17:20Z"},{"alias_kind":"pith_short_8","alias_value":"5SXMYKCX","created_at":"2026-07-05T04:17:20Z"}],"graph_snapshots":[{"event_id":"sha256:3fc401ef024fededfc420156dcdc37eb4d7d0254f7b2cea3deee7d04e24e267a","target":"graph","created_at":"2026-07-05T04:17:20Z","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/2202.00291/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multiple critical scenarios (like Wikipedia text generation given English Infoboxes) need automated generation of descriptive text in low resource (LR) languages from English fact triples. Previous work has focused on English fact-to-text (F2T) generation. To the best of our knowledge, there has been no previous attempt on cross-lingual alignment or generation for LR languages. Building an effective cross-lingual F2T (XF2T) system requires alignment between English structured facts and LR sentences. We propose two unsupervised methods for cross-lingual alignment. We contribute XALIGN, an XF2T ","authors_text":"Anubhav Sharma, Bhavyajeet Singh, Manish Gupta, Shivprasad Sagare, Tushar Abhishek, Vasudeva Varma","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-02-01T09:41:59Z","title":"XAlign: Cross-lingual Fact-to-Text Alignment and Generation for Low-Resource Languages"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.00291","kind":"arxiv","version":2},"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":"sha256:80ecafaab0f309ae25028dde145bc6d33b0a3d34a5122421aaaae30244abe61c","target":"record","created_at":"2026-07-05T04:17:20Z","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":"d4d10c716e659b3f27124fe19593ed336c6409aaa642120d4541373a4127a8c1","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-02-01T09:41:59Z","title_canon_sha256":"6938d4fdb9a4b5e18fef1243c80f945d6feb2513420f8bc73b6cbe60f3501c76"},"schema_version":"1.0","source":{"id":"2202.00291","kind":"arxiv","version":2}},"canonical_sha256":"ecaecc2857c2665203f66938f8d1ca841641e0f2c8cd752af62f2d6d615e7640","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ecaecc2857c2665203f66938f8d1ca841641e0f2c8cd752af62f2d6d615e7640","first_computed_at":"2026-07-05T04:17:20.446661Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:17:20.446661Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rIx9lacCDm/0151c7CQwlN3HtxPpn6WFwis3w7gzKVxhlrPiwijVa6+zdaJ3ERlht5IwU5+Oq1RThX+6lMlkAg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:17:20.447137Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.00291","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:80ecafaab0f309ae25028dde145bc6d33b0a3d34a5122421aaaae30244abe61c","sha256:3fc401ef024fededfc420156dcdc37eb4d7d0254f7b2cea3deee7d04e24e267a"],"state_sha256":"c88fc93fdac94d99079c6cf782224ddbe84ddab153d149101502472c624f9609"}