{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:FTNTHYJC5NFUE6BHSILDNM6BHS","short_pith_number":"pith:FTNTHYJC","canonical_record":{"source":{"id":"2402.16694","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T16:09:00Z","cross_cats_sorted":["cs.PL","cs.SE"],"title_canon_sha256":"e596d4dec99582ba8ce93c471f0d85776a2cfe3ee954a4ff2d6e19ad829e4aec","abstract_canon_sha256":"08cf1e9f7993eea283b048d17d149990e3a8571a43e35daa6593e7a32fdef5be"},"schema_version":"1.0"},"canonical_sha256":"2cdb33e122eb4b427827921636b3c13c98df2295c8042475938dff66a1facf2d","source":{"kind":"arxiv","id":"2402.16694","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.16694","created_at":"2026-07-05T08:00:01Z"},{"alias_kind":"arxiv_version","alias_value":"2402.16694v2","created_at":"2026-07-05T08:00:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.16694","created_at":"2026-07-05T08:00:01Z"},{"alias_kind":"pith_short_12","alias_value":"FTNTHYJC5NFU","created_at":"2026-07-05T08:00:01Z"},{"alias_kind":"pith_short_16","alias_value":"FTNTHYJC5NFUE6BH","created_at":"2026-07-05T08:00:01Z"},{"alias_kind":"pith_short_8","alias_value":"FTNTHYJC","created_at":"2026-07-05T08:00:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:FTNTHYJC5NFUE6BHSILDNM6BHS","target":"record","payload":{"canonical_record":{"source":{"id":"2402.16694","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T16:09:00Z","cross_cats_sorted":["cs.PL","cs.SE"],"title_canon_sha256":"e596d4dec99582ba8ce93c471f0d85776a2cfe3ee954a4ff2d6e19ad829e4aec","abstract_canon_sha256":"08cf1e9f7993eea283b048d17d149990e3a8571a43e35daa6593e7a32fdef5be"},"schema_version":"1.0"},"canonical_sha256":"2cdb33e122eb4b427827921636b3c13c98df2295c8042475938dff66a1facf2d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:00:01.962861Z","signature_b64":"RJTbMLSUcrMpm32DIOrHSiUecJ7fni7gh0aQ2Fdqn8WAs7+r0GjKiKlhJ9DLp2sogOlsTZ3eUXou/mZRZnPZCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2cdb33e122eb4b427827921636b3c13c98df2295c8042475938dff66a1facf2d","last_reissued_at":"2026-07-05T08:00:01.962364Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:00:01.962364Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.16694","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":"2026-07-05T08:00:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S5zukaMbEM7LjUtcC2NPObspfzMb8VWC7wB6jSR5afaOzxv1OqMndqNpj9I0dkdwLErmDF24+ZZp2oFyO+PHDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T20:27:03.700658Z"},"content_sha256":"01a8c9ae24d5d192d6ebe1bf0eae735fa7341ca74789b5193ef3998ab0967807","schema_version":"1.0","event_id":"sha256:01a8c9ae24d5d192d6ebe1bf0eae735fa7341ca74789b5193ef3998ab0967807"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:FTNTHYJC5NFUE6BHSILDNM6BHS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"HumanEval-XL: A Multilingual Code Generation Benchmark for Cross-lingual Natural Language Generalization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.PL","cs.SE"],"primary_cat":"cs.CL","authors_text":"Qiwei Peng, Xuhong Li, Yekun Chai","submitted_at":"2024-02-26T16:09:00Z","abstract_excerpt":"Large language models (LLMs) have made significant progress in generating codes from textual prompts. However, existing benchmarks have mainly concentrated on translating English prompts to multilingual codes or have been constrained to very limited natural languages (NLs). These benchmarks have overlooked the vast landscape of massively multilingual NL to multilingual code, leaving a critical gap in the evaluation of multilingual LLMs. In response, we introduce HumanEval-XL, a massively multilingual code generation benchmark specifically crafted to address this deficiency. HumanEval-XL establ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.16694","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/2402.16694/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":"2026-07-05T08:00:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lNu5f5hRTwtJ0YwZ3eQNCrX1kwXr0WoIy/ZieW1QUyoIHs12VcwM6g2q3A7UH4+5T5wvOgXBQS0y8rKj6edpDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T20:27:03.701023Z"},"content_sha256":"6168d9dc8c55356b07146189e2d458b5ee06855418849e9923d304c894e30a0d","schema_version":"1.0","event_id":"sha256:6168d9dc8c55356b07146189e2d458b5ee06855418849e9923d304c894e30a0d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FTNTHYJC5NFUE6BHSILDNM6BHS/bundle.json","state_url":"https://pith.science/pith/FTNTHYJC5NFUE6BHSILDNM6BHS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FTNTHYJC5NFUE6BHSILDNM6BHS/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":"2026-07-06T20:27:03Z","links":{"resolver":"https://pith.science/pith/FTNTHYJC5NFUE6BHSILDNM6BHS","bundle":"https://pith.science/pith/FTNTHYJC5NFUE6BHSILDNM6BHS/bundle.json","state":"https://pith.science/pith/FTNTHYJC5NFUE6BHSILDNM6BHS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FTNTHYJC5NFUE6BHSILDNM6BHS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:FTNTHYJC5NFUE6BHSILDNM6BHS","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":"08cf1e9f7993eea283b048d17d149990e3a8571a43e35daa6593e7a32fdef5be","cross_cats_sorted":["cs.PL","cs.SE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T16:09:00Z","title_canon_sha256":"e596d4dec99582ba8ce93c471f0d85776a2cfe3ee954a4ff2d6e19ad829e4aec"},"schema_version":"1.0","source":{"id":"2402.16694","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.16694","created_at":"2026-07-05T08:00:01Z"},{"alias_kind":"arxiv_version","alias_value":"2402.16694v2","created_at":"2026-07-05T08:00:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.16694","created_at":"2026-07-05T08:00:01Z"},{"alias_kind":"pith_short_12","alias_value":"FTNTHYJC5NFU","created_at":"2026-07-05T08:00:01Z"},{"alias_kind":"pith_short_16","alias_value":"FTNTHYJC5NFUE6BH","created_at":"2026-07-05T08:00:01Z"},{"alias_kind":"pith_short_8","alias_value":"FTNTHYJC","created_at":"2026-07-05T08:00:01Z"}],"graph_snapshots":[{"event_id":"sha256:6168d9dc8c55356b07146189e2d458b5ee06855418849e9923d304c894e30a0d","target":"graph","created_at":"2026-07-05T08:00:01Z","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/2402.16694/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) have made significant progress in generating codes from textual prompts. However, existing benchmarks have mainly concentrated on translating English prompts to multilingual codes or have been constrained to very limited natural languages (NLs). These benchmarks have overlooked the vast landscape of massively multilingual NL to multilingual code, leaving a critical gap in the evaluation of multilingual LLMs. In response, we introduce HumanEval-XL, a massively multilingual code generation benchmark specifically crafted to address this deficiency. HumanEval-XL establ","authors_text":"Qiwei Peng, Xuhong Li, Yekun Chai","cross_cats":["cs.PL","cs.SE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T16:09:00Z","title":"HumanEval-XL: A Multilingual Code Generation Benchmark for Cross-lingual Natural Language Generalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.16694","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":"sha256:01a8c9ae24d5d192d6ebe1bf0eae735fa7341ca74789b5193ef3998ab0967807","target":"record","created_at":"2026-07-05T08:00:01Z","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":"08cf1e9f7993eea283b048d17d149990e3a8571a43e35daa6593e7a32fdef5be","cross_cats_sorted":["cs.PL","cs.SE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T16:09:00Z","title_canon_sha256":"e596d4dec99582ba8ce93c471f0d85776a2cfe3ee954a4ff2d6e19ad829e4aec"},"schema_version":"1.0","source":{"id":"2402.16694","kind":"arxiv","version":2}},"canonical_sha256":"2cdb33e122eb4b427827921636b3c13c98df2295c8042475938dff66a1facf2d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2cdb33e122eb4b427827921636b3c13c98df2295c8042475938dff66a1facf2d","first_computed_at":"2026-07-05T08:00:01.962364Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:00:01.962364Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RJTbMLSUcrMpm32DIOrHSiUecJ7fni7gh0aQ2Fdqn8WAs7+r0GjKiKlhJ9DLp2sogOlsTZ3eUXou/mZRZnPZCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:00:01.962861Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.16694","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:01a8c9ae24d5d192d6ebe1bf0eae735fa7341ca74789b5193ef3998ab0967807","sha256:6168d9dc8c55356b07146189e2d458b5ee06855418849e9923d304c894e30a0d"],"state_sha256":"8a56997b6c1c5ea87bfc8fb75c026182de4f9ec8b907c48113804b6e527e38aa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"anC2K2LAD9LuLAI3oUBSQeeECMI6OXTY00qB5Yu/HeHadDoJ/8bYkqettFJ6fRLUYe/ZGtIcpEOhprLgKPQ8Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T20:27:03.703004Z","bundle_sha256":"351e5ab6fd609b27c4b3a2993b60743e3571caeaf17deac23b2cf115471e701e"}}