{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:NZBLRWBEQQ4G7VKHNS45EPLJML","short_pith_number":"pith:NZBLRWBE","canonical_record":{"source":{"id":"2410.04407","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-10-06T08:51:30Z","cross_cats_sorted":[],"title_canon_sha256":"7cd06b724744a6a4e9a37b466d5d3988d7213cef586ac49d5848e6bb2b0d63cb","abstract_canon_sha256":"67cba0d2b1e729eddd79cda12c30d4b16b87e2ec9388b1351044f067f35540b4"},"schema_version":"1.0"},"canonical_sha256":"6e42b8d82484386fd5476cb9d23d6962d840cf8285630764f34e7e979dfc2994","source":{"kind":"arxiv","id":"2410.04407","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04407","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04407v2","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04407","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_12","alias_value":"NZBLRWBEQQ4G","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_16","alias_value":"NZBLRWBEQQ4G7VKH","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_8","alias_value":"NZBLRWBE","created_at":"2026-07-05T11:09:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:NZBLRWBEQQ4G7VKHNS45EPLJML","target":"record","payload":{"canonical_record":{"source":{"id":"2410.04407","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-10-06T08:51:30Z","cross_cats_sorted":[],"title_canon_sha256":"7cd06b724744a6a4e9a37b466d5d3988d7213cef586ac49d5848e6bb2b0d63cb","abstract_canon_sha256":"67cba0d2b1e729eddd79cda12c30d4b16b87e2ec9388b1351044f067f35540b4"},"schema_version":"1.0"},"canonical_sha256":"6e42b8d82484386fd5476cb9d23d6962d840cf8285630764f34e7e979dfc2994","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:09:01.241781Z","signature_b64":"Ob+D0SRHgSmEN26vMt1H63sxb5AYsPPFUOFIk9uQYBrVHdigS+fpIChfY5YB+iSJy97c0eT+GnojjgmCSwFSCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6e42b8d82484386fd5476cb9d23d6962d840cf8285630764f34e7e979dfc2994","last_reissued_at":"2026-07-05T11:09:01.241252Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:09:01.241252Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.04407","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:09:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+FgGtv2m6Bo5FSvsQuHIhYKdvd9Ou1p5H+bKCLfTuDmfgrvk7E9dTNe7ZEdPyO2mULViCK01ez8GtUP4Y+h2BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T03:22:48.157273Z"},"content_sha256":"97430897950a5bca0f8752653e81c8da0d89a08988a80cbed482f8be684534f2","schema_version":"1.0","event_id":"sha256:97430897950a5bca0f8752653e81c8da0d89a08988a80cbed482f8be684534f2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:NZBLRWBEQQ4G7VKHNS45EPLJML","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Lens: Rethinking Multilingual Enhancement for Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Bing Qin, Jiahe Guo, Ting Liu, Tongtong Wu, Wanxiang Che, Weixiang Zhao, Xingyu Sui, Yang Deng, Yanyan Zhao, Yulin Hu","submitted_at":"2024-10-06T08:51:30Z","abstract_excerpt":"As global demand for multilingual large language models (LLMs) grows, most LLMs still remain overly focused on English, leading to the limited access to advanced AI for non-English speakers. Current methods to enhance multilingual capabilities largely rely on data-driven post-training techniques, such as multilingual instruction tuning or continual pre-training. However, these approaches exhibit significant limitations, including high resource cost, exacerbation of off-target issue and catastrophic forgetting of central language abilities. To this end, we propose Lens, a novel approach that en"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04407","kind":"arxiv","version":2},"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/2410.04407/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:09:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zkX02xElh19uqmulx2AFFIkJ4zJB/buCH8hLIyIZZtZcVmy5vtVODg79KshX8OlXdvk9m/UPvOlKaODjlecdBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T03:22:48.157658Z"},"content_sha256":"f3a020351c79643a6dd16a1f8ff04a30f1e8caebf105358593bb52002cbc56ed","schema_version":"1.0","event_id":"sha256:f3a020351c79643a6dd16a1f8ff04a30f1e8caebf105358593bb52002cbc56ed"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NZBLRWBEQQ4G7VKHNS45EPLJML/bundle.json","state_url":"https://pith.science/pith/NZBLRWBEQQ4G7VKHNS45EPLJML/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NZBLRWBEQQ4G7VKHNS45EPLJML/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-19T03:22:48Z","links":{"resolver":"https://pith.science/pith/NZBLRWBEQQ4G7VKHNS45EPLJML","bundle":"https://pith.science/pith/NZBLRWBEQQ4G7VKHNS45EPLJML/bundle.json","state":"https://pith.science/pith/NZBLRWBEQQ4G7VKHNS45EPLJML/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NZBLRWBEQQ4G7VKHNS45EPLJML/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NZBLRWBEQQ4G7VKHNS45EPLJML","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":"67cba0d2b1e729eddd79cda12c30d4b16b87e2ec9388b1351044f067f35540b4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-10-06T08:51:30Z","title_canon_sha256":"7cd06b724744a6a4e9a37b466d5d3988d7213cef586ac49d5848e6bb2b0d63cb"},"schema_version":"1.0","source":{"id":"2410.04407","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04407","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04407v2","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04407","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_12","alias_value":"NZBLRWBEQQ4G","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_16","alias_value":"NZBLRWBEQQ4G7VKH","created_at":"2026-07-05T11:09:01Z"},{"alias_kind":"pith_short_8","alias_value":"NZBLRWBE","created_at":"2026-07-05T11:09:01Z"}],"graph_snapshots":[{"event_id":"sha256:f3a020351c79643a6dd16a1f8ff04a30f1e8caebf105358593bb52002cbc56ed","target":"graph","created_at":"2026-07-05T11:09:01Z","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/2410.04407/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As global demand for multilingual large language models (LLMs) grows, most LLMs still remain overly focused on English, leading to the limited access to advanced AI for non-English speakers. Current methods to enhance multilingual capabilities largely rely on data-driven post-training techniques, such as multilingual instruction tuning or continual pre-training. However, these approaches exhibit significant limitations, including high resource cost, exacerbation of off-target issue and catastrophic forgetting of central language abilities. To this end, we propose Lens, a novel approach that en","authors_text":"Bing Qin, Jiahe Guo, Ting Liu, Tongtong Wu, Wanxiang Che, Weixiang Zhao, Xingyu Sui, Yang Deng, Yanyan Zhao, Yulin Hu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-10-06T08:51:30Z","title":"Lens: Rethinking Multilingual Enhancement for Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04407","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":"sha256:97430897950a5bca0f8752653e81c8da0d89a08988a80cbed482f8be684534f2","target":"record","created_at":"2026-07-05T11:09:01Z","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":"67cba0d2b1e729eddd79cda12c30d4b16b87e2ec9388b1351044f067f35540b4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-10-06T08:51:30Z","title_canon_sha256":"7cd06b724744a6a4e9a37b466d5d3988d7213cef586ac49d5848e6bb2b0d63cb"},"schema_version":"1.0","source":{"id":"2410.04407","kind":"arxiv","version":2}},"canonical_sha256":"6e42b8d82484386fd5476cb9d23d6962d840cf8285630764f34e7e979dfc2994","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6e42b8d82484386fd5476cb9d23d6962d840cf8285630764f34e7e979dfc2994","first_computed_at":"2026-07-05T11:09:01.241252Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:09:01.241252Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ob+D0SRHgSmEN26vMt1H63sxb5AYsPPFUOFIk9uQYBrVHdigS+fpIChfY5YB+iSJy97c0eT+GnojjgmCSwFSCg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:09:01.241781Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.04407","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:97430897950a5bca0f8752653e81c8da0d89a08988a80cbed482f8be684534f2","sha256:f3a020351c79643a6dd16a1f8ff04a30f1e8caebf105358593bb52002cbc56ed"],"state_sha256":"459d3df08331f82800512fa144098870555edb8513880dd9910583ff2746fac2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UA9BaMUk76XlbNw3E/U/HIuBMvLt5qyqy/FUNmoEPppanYCp6IKAZq/pCM7nvUHUX5pDnYjIkziQFZpLyfD4DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-19T03:22:48.159854Z","bundle_sha256":"d836ecb92fcdd48d60bf5f4317bcce33305ca28901d475101c63f7e29388e354"}}