{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HGKVMVVQLAMRFAL74RPU5CYNSA","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":"e12589056e4ffbaa1cf53e6b224ecfe1300d5b247ac0c9955ca169b06308d652","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-27T18:06:25Z","title_canon_sha256":"9380cd5eaa9d9a10ee2476d3db18101fe06f2f30bd92aac7062a39fce3933498"},"schema_version":"1.0","source":{"id":"2412.19770","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.19770","created_at":"2026-07-05T10:08:26Z"},{"alias_kind":"arxiv_version","alias_value":"2412.19770v2","created_at":"2026-07-05T10:08:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.19770","created_at":"2026-07-05T10:08:26Z"},{"alias_kind":"pith_short_12","alias_value":"HGKVMVVQLAMR","created_at":"2026-07-05T10:08:26Z"},{"alias_kind":"pith_short_16","alias_value":"HGKVMVVQLAMRFAL7","created_at":"2026-07-05T10:08:26Z"},{"alias_kind":"pith_short_8","alias_value":"HGKVMVVQ","created_at":"2026-07-05T10:08:26Z"}],"graph_snapshots":[{"event_id":"sha256:ee1a564c26f4f5eae320c984b689fff2e5f8f56bf74e78d4003b2d2eeb8938ed","target":"graph","created_at":"2026-07-05T10:08:26Z","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/2412.19770/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Translating legacy Fortran code into C++ is a crucial step in modernizing high-performance computing (HPC) applications. However, the scarcity of high-quality, parallel Fortran-to-C++ datasets and the limited domain-specific expertise in large language models (LLMs) present significant challenges for automated translation. In this paper, we introduce Fortran2CPP, a multi-turn dialogue dataset generated by a novel LLM agent-based approach that integrates a dual-LLM Questioner-Solver module to enhance translation accuracy. Our dataset comprises 11.7k dialogues capturing iterative feedback-decisi","authors_text":"Ali Jannesari, Bin Lei, Caiwen Ding, Chunhua Liao, Dunzhi Zhou, Le Chen, Pei-Hung Lin","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-27T18:06:25Z","title":"Fortran2CPP: Automating Fortran-to-C++ Translation using LLMs via Multi-Turn Dialogue and Dual-Agent Integration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.19770","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:bee57730a05371637160f83527413d1b63ea45eca2614e0f0e1efd415430c6fb","target":"record","created_at":"2026-07-05T10:08:26Z","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":"e12589056e4ffbaa1cf53e6b224ecfe1300d5b247ac0c9955ca169b06308d652","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-27T18:06:25Z","title_canon_sha256":"9380cd5eaa9d9a10ee2476d3db18101fe06f2f30bd92aac7062a39fce3933498"},"schema_version":"1.0","source":{"id":"2412.19770","kind":"arxiv","version":2}},"canonical_sha256":"39955656b0581912817fe45f4e8b0d9039c9637de772b79580b0a14c0ee1efdf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"39955656b0581912817fe45f4e8b0d9039c9637de772b79580b0a14c0ee1efdf","first_computed_at":"2026-07-05T10:08:26.840925Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:08:26.840925Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"q1Fhvdhlc9faIzfTydEUmcTWrw0K1ETYJ00gI4AEoclN06A05tkQuSUJZr8ZfbspKK8c+Gg1JwcSVQG+wLwgCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:08:26.841407Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.19770","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bee57730a05371637160f83527413d1b63ea45eca2614e0f0e1efd415430c6fb","sha256:ee1a564c26f4f5eae320c984b689fff2e5f8f56bf74e78d4003b2d2eeb8938ed"],"state_sha256":"ca0496a19ad4d1760978c80f25154f17e743b421cc5950d95f92f0707e17dbcb"}