{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:SJ7RMP3ORX56XU2PKZ6V425OUZ","short_pith_number":"pith:SJ7RMP3O","schema_version":"1.0","canonical_sha256":"927f163f6e8dfbebd34f567d5e6baea64ae423248cf98bf09dfa882a2e47d835","source":{"kind":"arxiv","id":"2308.16824","version":2},"attestation_state":"computed","paper":{"title":"Can Programming Languages Boost Each Other via Instruction Tuning?","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.PL","cs.SE"],"primary_cat":"cs.CL","authors_text":"Ailun Yu, Bei Chen, Bing Geng, Bo Shen, Daoguang Zan, Jiaxin Zhang, Jichuan Ji, Qianxiang Wang, Taihong Chen, Yafen Yao, Yongji Wang","submitted_at":"2023-08-31T15:53:51Z","abstract_excerpt":"When human programmers have mastered a programming language, it would be easier when they learn a new programming language. In this report, we focus on exploring whether programming languages can boost each other during the instruction fine-tuning phase of code large language models. We conduct extensive experiments of 8 popular programming languages (Python, JavaScript, TypeScript, C, C++, Java, Go, HTML) on StarCoder. Results demonstrate that programming languages can significantly improve each other. For example, CodeM-Python 15B trained on Python is able to increase Java by an absolute 17."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2308.16824","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-08-31T15:53:51Z","cross_cats_sorted":["cs.AI","cs.PL","cs.SE"],"title_canon_sha256":"22ac3f24c9cc053c4951d9ec6b29d15979548aa7de67d1b397f01614a2867b83","abstract_canon_sha256":"e929942ce4ea80773e5d25abdec6256aa5b6b913ed0b9df455883669d9672fbd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:47:28.518219Z","signature_b64":"vvH8e2Z7nwYSOcMT5p/vbo0K7kE7da8LPq172s8M2fkZYVV70SO3SITxec84H+AHQOo4dzwtpeyMOJGWS0q0Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"927f163f6e8dfbebd34f567d5e6baea64ae423248cf98bf09dfa882a2e47d835","last_reissued_at":"2026-07-05T06:47:28.517704Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:47:28.517704Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Can Programming Languages Boost Each Other via Instruction Tuning?","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.PL","cs.SE"],"primary_cat":"cs.CL","authors_text":"Ailun Yu, Bei Chen, Bing Geng, Bo Shen, Daoguang Zan, Jiaxin Zhang, Jichuan Ji, Qianxiang Wang, Taihong Chen, Yafen Yao, Yongji Wang","submitted_at":"2023-08-31T15:53:51Z","abstract_excerpt":"When human programmers have mastered a programming language, it would be easier when they learn a new programming language. In this report, we focus on exploring whether programming languages can boost each other during the instruction fine-tuning phase of code large language models. We conduct extensive experiments of 8 popular programming languages (Python, JavaScript, TypeScript, C, C++, Java, Go, HTML) on StarCoder. Results demonstrate that programming languages can significantly improve each other. For example, CodeM-Python 15B trained on Python is able to increase Java by an absolute 17."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.16824","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/2308.16824/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2308.16824","created_at":"2026-07-05T06:47:28.517768+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.16824v2","created_at":"2026-07-05T06:47:28.517768+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.16824","created_at":"2026-07-05T06:47:28.517768+00:00"},{"alias_kind":"pith_short_12","alias_value":"SJ7RMP3ORX56","created_at":"2026-07-05T06:47:28.517768+00:00"},{"alias_kind":"pith_short_16","alias_value":"SJ7RMP3ORX56XU2P","created_at":"2026-07-05T06:47:28.517768+00:00"},{"alias_kind":"pith_short_8","alias_value":"SJ7RMP3O","created_at":"2026-07-05T06:47:28.517768+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SJ7RMP3ORX56XU2PKZ6V425OUZ","json":"https://pith.science/pith/SJ7RMP3ORX56XU2PKZ6V425OUZ.json","graph_json":"https://pith.science/api/pith-number/SJ7RMP3ORX56XU2PKZ6V425OUZ/graph.json","events_json":"https://pith.science/api/pith-number/SJ7RMP3ORX56XU2PKZ6V425OUZ/events.json","paper":"https://pith.science/paper/SJ7RMP3O"},"agent_actions":{"view_html":"https://pith.science/pith/SJ7RMP3ORX56XU2PKZ6V425OUZ","download_json":"https://pith.science/pith/SJ7RMP3ORX56XU2PKZ6V425OUZ.json","view_paper":"https://pith.science/paper/SJ7RMP3O","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.16824&json=true","fetch_graph":"https://pith.science/api/pith-number/SJ7RMP3ORX56XU2PKZ6V425OUZ/graph.json","fetch_events":"https://pith.science/api/pith-number/SJ7RMP3ORX56XU2PKZ6V425OUZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SJ7RMP3ORX56XU2PKZ6V425OUZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SJ7RMP3ORX56XU2PKZ6V425OUZ/action/storage_attestation","attest_author":"https://pith.science/pith/SJ7RMP3ORX56XU2PKZ6V425OUZ/action/author_attestation","sign_citation":"https://pith.science/pith/SJ7RMP3ORX56XU2PKZ6V425OUZ/action/citation_signature","submit_replication":"https://pith.science/pith/SJ7RMP3ORX56XU2PKZ6V425OUZ/action/replication_record"}},"created_at":"2026-07-05T06:47:28.517768+00:00","updated_at":"2026-07-05T06:47:28.517768+00:00"}