{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:2DSGSZYMTUCTDOJ66MFRMBI2ZQ","short_pith_number":"pith:2DSGSZYM","canonical_record":{"source":{"id":"2403.03894","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-06T17:52:08Z","cross_cats_sorted":["cs.CL","cs.PL"],"title_canon_sha256":"4b5196ebda71353351548dc1893c0b4f24e3f259dd378df2421b85d920d37cdb","abstract_canon_sha256":"8bb7719dd8e030c2bddab919bdf83175cd3befb6527536eb35a3dbfa05fa952e"},"schema_version":"1.0"},"canonical_sha256":"d0e469670c9d0531b93ef30b16051acc24fab6146fc529c0a32657a76a9644d1","source":{"kind":"arxiv","id":"2403.03894","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.03894","created_at":"2026-07-05T08:08:02Z"},{"alias_kind":"arxiv_version","alias_value":"2403.03894v3","created_at":"2026-07-05T08:08:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.03894","created_at":"2026-07-05T08:08:02Z"},{"alias_kind":"pith_short_12","alias_value":"2DSGSZYMTUCT","created_at":"2026-07-05T08:08:02Z"},{"alias_kind":"pith_short_16","alias_value":"2DSGSZYMTUCTDOJ6","created_at":"2026-07-05T08:08:02Z"},{"alias_kind":"pith_short_8","alias_value":"2DSGSZYM","created_at":"2026-07-05T08:08:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:2DSGSZYMTUCTDOJ66MFRMBI2ZQ","target":"record","payload":{"canonical_record":{"source":{"id":"2403.03894","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-06T17:52:08Z","cross_cats_sorted":["cs.CL","cs.PL"],"title_canon_sha256":"4b5196ebda71353351548dc1893c0b4f24e3f259dd378df2421b85d920d37cdb","abstract_canon_sha256":"8bb7719dd8e030c2bddab919bdf83175cd3befb6527536eb35a3dbfa05fa952e"},"schema_version":"1.0"},"canonical_sha256":"d0e469670c9d0531b93ef30b16051acc24fab6146fc529c0a32657a76a9644d1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:08:02.240787Z","signature_b64":"A+BZE/2xfJRB0VPgn8Jd+LOZcf4MYWXXbhwpilxLbsjRESfANB7a4fPVBaSJofsCr3hF+Y2d034hfgS/3yQhBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d0e469670c9d0531b93ef30b16051acc24fab6146fc529c0a32657a76a9644d1","last_reissued_at":"2026-07-05T08:08:02.240325Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:08:02.240325Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.03894","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:08:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CAD8BnQ+PN9RLj3gvhTP775Fh3EnnHmmfHebG69MvGEXLN1PhAB7zlxwYM1JjvZK0TSC+XkGCCkhfqM/MCbRDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T12:41:14.599367Z"},"content_sha256":"862d395d0436d6a09dadaa92a86dc4d71574e37e5599d8c939816e7c21f13988","schema_version":"1.0","event_id":"sha256:862d395d0436d6a09dadaa92a86dc4d71574e37e5599d8c939816e7c21f13988"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:2DSGSZYMTUCTDOJ66MFRMBI2ZQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL","cs.PL"],"primary_cat":"cs.AI","authors_text":"Goran Glava\\v{s}, Indraneil Paul, Iryna Gurevych","submitted_at":"2024-03-06T17:52:08Z","abstract_excerpt":"Code understanding and generation have fast become some of the most popular applications of language models (LMs). Nonetheless, research on multilingual aspects of Code-LMs (i.e., LMs for code generation) such as cross-lingual transfer between different programming languages, language-specific data augmentation, and post-hoc LM adaptation, alongside exploitation of data sources other than the original textual content, has been much sparser than for their natural language counterparts. In particular, most mainstream Code-LMs have been pre-trained on source code files alone. In this work, we inv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.03894","kind":"arxiv","version":3},"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/2403.03894/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":"2026-07-05T08:08:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C9XfnJnbRu5Y04baPirPXHudfrl7dsYHE+b5Ao8OJkgVvY88kKPi9uPz65CLrzoLr4cMjxNkiMsqoYkFr0W8AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T12:41:14.599873Z"},"content_sha256":"b8460270fc8f2674d2c8722ed7e2938e19f012afb81e16e9ed534e1c8261eb7f","schema_version":"1.0","event_id":"sha256:b8460270fc8f2674d2c8722ed7e2938e19f012afb81e16e9ed534e1c8261eb7f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2DSGSZYMTUCTDOJ66MFRMBI2ZQ/bundle.json","state_url":"https://pith.science/pith/2DSGSZYMTUCTDOJ66MFRMBI2ZQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2DSGSZYMTUCTDOJ66MFRMBI2ZQ/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":"2026-08-07T12:41:14Z","links":{"resolver":"https://pith.science/pith/2DSGSZYMTUCTDOJ66MFRMBI2ZQ","bundle":"https://pith.science/pith/2DSGSZYMTUCTDOJ66MFRMBI2ZQ/bundle.json","state":"https://pith.science/pith/2DSGSZYMTUCTDOJ66MFRMBI2ZQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2DSGSZYMTUCTDOJ66MFRMBI2ZQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:2DSGSZYMTUCTDOJ66MFRMBI2ZQ","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":"8bb7719dd8e030c2bddab919bdf83175cd3befb6527536eb35a3dbfa05fa952e","cross_cats_sorted":["cs.CL","cs.PL"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-06T17:52:08Z","title_canon_sha256":"4b5196ebda71353351548dc1893c0b4f24e3f259dd378df2421b85d920d37cdb"},"schema_version":"1.0","source":{"id":"2403.03894","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.03894","created_at":"2026-07-05T08:08:02Z"},{"alias_kind":"arxiv_version","alias_value":"2403.03894v3","created_at":"2026-07-05T08:08:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.03894","created_at":"2026-07-05T08:08:02Z"},{"alias_kind":"pith_short_12","alias_value":"2DSGSZYMTUCT","created_at":"2026-07-05T08:08:02Z"},{"alias_kind":"pith_short_16","alias_value":"2DSGSZYMTUCTDOJ6","created_at":"2026-07-05T08:08:02Z"},{"alias_kind":"pith_short_8","alias_value":"2DSGSZYM","created_at":"2026-07-05T08:08:02Z"}],"graph_snapshots":[{"event_id":"sha256:b8460270fc8f2674d2c8722ed7e2938e19f012afb81e16e9ed534e1c8261eb7f","target":"graph","created_at":"2026-07-05T08:08:02Z","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/2403.03894/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Code understanding and generation have fast become some of the most popular applications of language models (LMs). Nonetheless, research on multilingual aspects of Code-LMs (i.e., LMs for code generation) such as cross-lingual transfer between different programming languages, language-specific data augmentation, and post-hoc LM adaptation, alongside exploitation of data sources other than the original textual content, has been much sparser than for their natural language counterparts. In particular, most mainstream Code-LMs have been pre-trained on source code files alone. In this work, we inv","authors_text":"Goran Glava\\v{s}, Indraneil Paul, Iryna Gurevych","cross_cats":["cs.CL","cs.PL"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-06T17:52:08Z","title":"IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.03894","kind":"arxiv","version":3},"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":"sha256:862d395d0436d6a09dadaa92a86dc4d71574e37e5599d8c939816e7c21f13988","target":"record","created_at":"2026-07-05T08:08:02Z","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":"8bb7719dd8e030c2bddab919bdf83175cd3befb6527536eb35a3dbfa05fa952e","cross_cats_sorted":["cs.CL","cs.PL"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-06T17:52:08Z","title_canon_sha256":"4b5196ebda71353351548dc1893c0b4f24e3f259dd378df2421b85d920d37cdb"},"schema_version":"1.0","source":{"id":"2403.03894","kind":"arxiv","version":3}},"canonical_sha256":"d0e469670c9d0531b93ef30b16051acc24fab6146fc529c0a32657a76a9644d1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d0e469670c9d0531b93ef30b16051acc24fab6146fc529c0a32657a76a9644d1","first_computed_at":"2026-07-05T08:08:02.240325Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:08:02.240325Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"A+BZE/2xfJRB0VPgn8Jd+LOZcf4MYWXXbhwpilxLbsjRESfANB7a4fPVBaSJofsCr3hF+Y2d034hfgS/3yQhBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:08:02.240787Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.03894","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:862d395d0436d6a09dadaa92a86dc4d71574e37e5599d8c939816e7c21f13988","sha256:b8460270fc8f2674d2c8722ed7e2938e19f012afb81e16e9ed534e1c8261eb7f"],"state_sha256":"171813c49035242aedb7105f0d832fbcb08fa0953152e41c29c4e42dfd294635"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yXktreyWVXnOwPo8AnTBGE2qkKEVHkef9WArnXjgpocADcQIQ1CD3hfzbraabV/MXQjT7LQ1ql8I6h51LeefCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T12:41:14.604030Z","bundle_sha256":"ec08218366126ac9f5b60e807f6426b4c3fc3aa51711b98a1b52835194f012bb"}}