{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:RPQVG4E6GTYP4AHELBTCSEO466","short_pith_number":"pith:RPQVG4E6","canonical_record":{"source":{"id":"2411.01141","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-02T05:10:50Z","cross_cats_sorted":[],"title_canon_sha256":"103f749ae12b95773db4bebdddef4ac263e2a59f5b7d20214db677799fed9dce","abstract_canon_sha256":"843e2a2733b142f996f7cadb18d0c6c13ec7f233b985936910f547d3e4b6460c"},"schema_version":"1.0"},"canonical_sha256":"8be153709e34f0fe00e458662911dcf78c45067d27142bde10212c29a5a58bcf","source":{"kind":"arxiv","id":"2411.01141","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.01141","created_at":"2026-05-21T01:04:12Z"},{"alias_kind":"arxiv_version","alias_value":"2411.01141v2","created_at":"2026-05-21T01:04:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.01141","created_at":"2026-05-21T01:04:12Z"},{"alias_kind":"pith_short_12","alias_value":"RPQVG4E6GTYP","created_at":"2026-05-21T01:04:12Z"},{"alias_kind":"pith_short_16","alias_value":"RPQVG4E6GTYP4AHE","created_at":"2026-05-21T01:04:12Z"},{"alias_kind":"pith_short_8","alias_value":"RPQVG4E6","created_at":"2026-05-21T01:04:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:RPQVG4E6GTYP4AHELBTCSEO466","target":"record","payload":{"canonical_record":{"source":{"id":"2411.01141","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-02T05:10:50Z","cross_cats_sorted":[],"title_canon_sha256":"103f749ae12b95773db4bebdddef4ac263e2a59f5b7d20214db677799fed9dce","abstract_canon_sha256":"843e2a2733b142f996f7cadb18d0c6c13ec7f233b985936910f547d3e4b6460c"},"schema_version":"1.0"},"canonical_sha256":"8be153709e34f0fe00e458662911dcf78c45067d27142bde10212c29a5a58bcf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-21T01:04:12.228701Z","signature_b64":"Tzf5qcY+2jw2vnePqiVnrJotqXqwZ8uHoKC8VhMvXIJmP+7p5jneQlXuJ/Jy1MlYSaGbLsp1qztzEnWSxrCXCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8be153709e34f0fe00e458662911dcf78c45067d27142bde10212c29a5a58bcf","last_reissued_at":"2026-05-21T01:04:12.227942Z","signature_status":"signed_v1","first_computed_at":"2026-05-21T01:04:12.227942Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.01141","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":"2026-05-21T01:04:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E6Xh5rRPTZtb++hs0imtRzES3qDBHDb7HAtuOtlONjdsKkecmHSZ9Z/9/tVTyYtFzQhbhvVlf8Y1+sVWcHxyBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T12:00:49.095882Z"},"content_sha256":"512637c0daa8d22f152c08ebe45688ade5bea587af324bbbb466eaa6a007633b","schema_version":"1.0","event_id":"sha256:512637c0daa8d22f152c08ebe45688ade5bea587af324bbbb466eaa6a007633b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:RPQVG4E6GTYP4AHELBTCSEO466","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dictionary Insertion Prompting for Multilingual Reasoning on Multilingual Large Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Hongyuan Lu, Wai Lam, Zixuan Li","submitted_at":"2024-11-02T05:10:50Z","abstract_excerpt":"There are two shortages in the current Large Language Models (LLMs) era. The first is short of multilingual models, where most LLMs are English-centric and performance is limited on multilingual reasoning. The second is the place of external knowledge to be used, where most retrieved knowledge is prepended to the user queries (maybe sub-optimal). This paper presents a novel and simple yet effective method called \\textbf{D}ictionary \\textbf{I}nsertion \\textbf{P}rompting (\\textbf{DIP}). When providing a non-English prompt, DIP looks up a word dictionary and inserts words' English counterparts in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.01141","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/2411.01141/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":"2026-05-21T01:04:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1yU/m48w8hpqmlC2qzHM60PV1cB/JQsvpmCaBimZCc8nTQkJNh6MnKVe0CPzWHiOTKbrdSt0WNkecTHJI+m+Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T12:00:49.096625Z"},"content_sha256":"d01b7a6b2df13c96b915c00a76c5ddb5421aba8ff36dd2eb549d2960d1e80bf0","schema_version":"1.0","event_id":"sha256:d01b7a6b2df13c96b915c00a76c5ddb5421aba8ff36dd2eb549d2960d1e80bf0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RPQVG4E6GTYP4AHELBTCSEO466/bundle.json","state_url":"https://pith.science/pith/RPQVG4E6GTYP4AHELBTCSEO466/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RPQVG4E6GTYP4AHELBTCSEO466/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":"2026-05-25T12:00:49Z","links":{"resolver":"https://pith.science/pith/RPQVG4E6GTYP4AHELBTCSEO466","bundle":"https://pith.science/pith/RPQVG4E6GTYP4AHELBTCSEO466/bundle.json","state":"https://pith.science/pith/RPQVG4E6GTYP4AHELBTCSEO466/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RPQVG4E6GTYP4AHELBTCSEO466/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:RPQVG4E6GTYP4AHELBTCSEO466","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":"843e2a2733b142f996f7cadb18d0c6c13ec7f233b985936910f547d3e4b6460c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-02T05:10:50Z","title_canon_sha256":"103f749ae12b95773db4bebdddef4ac263e2a59f5b7d20214db677799fed9dce"},"schema_version":"1.0","source":{"id":"2411.01141","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.01141","created_at":"2026-05-21T01:04:12Z"},{"alias_kind":"arxiv_version","alias_value":"2411.01141v2","created_at":"2026-05-21T01:04:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.01141","created_at":"2026-05-21T01:04:12Z"},{"alias_kind":"pith_short_12","alias_value":"RPQVG4E6GTYP","created_at":"2026-05-21T01:04:12Z"},{"alias_kind":"pith_short_16","alias_value":"RPQVG4E6GTYP4AHE","created_at":"2026-05-21T01:04:12Z"},{"alias_kind":"pith_short_8","alias_value":"RPQVG4E6","created_at":"2026-05-21T01:04:12Z"}],"graph_snapshots":[{"event_id":"sha256:d01b7a6b2df13c96b915c00a76c5ddb5421aba8ff36dd2eb549d2960d1e80bf0","target":"graph","created_at":"2026-05-21T01:04:12Z","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/2411.01141/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"There are two shortages in the current Large Language Models (LLMs) era. The first is short of multilingual models, where most LLMs are English-centric and performance is limited on multilingual reasoning. The second is the place of external knowledge to be used, where most retrieved knowledge is prepended to the user queries (maybe sub-optimal). This paper presents a novel and simple yet effective method called \\textbf{D}ictionary \\textbf{I}nsertion \\textbf{P}rompting (\\textbf{DIP}). When providing a non-English prompt, DIP looks up a word dictionary and inserts words' English counterparts in","authors_text":"Hongyuan Lu, Wai Lam, Zixuan Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-02T05:10:50Z","title":"Dictionary Insertion Prompting for Multilingual Reasoning on Multilingual Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.01141","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":"sha256:512637c0daa8d22f152c08ebe45688ade5bea587af324bbbb466eaa6a007633b","target":"record","created_at":"2026-05-21T01:04:12Z","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":"843e2a2733b142f996f7cadb18d0c6c13ec7f233b985936910f547d3e4b6460c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-02T05:10:50Z","title_canon_sha256":"103f749ae12b95773db4bebdddef4ac263e2a59f5b7d20214db677799fed9dce"},"schema_version":"1.0","source":{"id":"2411.01141","kind":"arxiv","version":2}},"canonical_sha256":"8be153709e34f0fe00e458662911dcf78c45067d27142bde10212c29a5a58bcf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8be153709e34f0fe00e458662911dcf78c45067d27142bde10212c29a5a58bcf","first_computed_at":"2026-05-21T01:04:12.227942Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-21T01:04:12.227942Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Tzf5qcY+2jw2vnePqiVnrJotqXqwZ8uHoKC8VhMvXIJmP+7p5jneQlXuJ/Jy1MlYSaGbLsp1qztzEnWSxrCXCw==","signature_status":"signed_v1","signed_at":"2026-05-21T01:04:12.228701Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.01141","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:512637c0daa8d22f152c08ebe45688ade5bea587af324bbbb466eaa6a007633b","sha256:d01b7a6b2df13c96b915c00a76c5ddb5421aba8ff36dd2eb549d2960d1e80bf0"],"state_sha256":"4fe370c939f6175dc9b6c6a1336f58c448e9cb76cc94670c715a4c9c2bfe5204"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ch2FAmOzWOHDF6TyuXt/sqN8dBpmQZ3+4+vvxJBC24rTMEJ+bROKgh9DBjl56KjHZd7Sa/QBJUfTvaFVqc5oCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T12:00:49.100606Z","bundle_sha256":"68f33acf4788d660971a30f684453ea1da03a7029c3cd330f3aa894eb6995131"}}