{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:5WRROBFLOGWMNWC2OZUZAJUAEN","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":"aabab9625cd34dcda2af581eb325bae1381a8f019e71f524630746426dd6a9bc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2021-03-31T22:36:41Z","title_canon_sha256":"56a44313e2d394651221434578bd53d0277394faefd6f4b2e6bfc2a7a1cbb6ca"},"schema_version":"1.0","source":{"id":"2104.01002","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.01002","created_at":"2026-07-05T03:12:47Z"},{"alias_kind":"arxiv_version","alias_value":"2104.01002v2","created_at":"2026-07-05T03:12:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.01002","created_at":"2026-07-05T03:12:47Z"},{"alias_kind":"pith_short_12","alias_value":"5WRROBFLOGWM","created_at":"2026-07-05T03:12:47Z"},{"alias_kind":"pith_short_16","alias_value":"5WRROBFLOGWMNWC2","created_at":"2026-07-05T03:12:47Z"},{"alias_kind":"pith_short_8","alias_value":"5WRROBFL","created_at":"2026-07-05T03:12:47Z"}],"graph_snapshots":[{"event_id":"sha256:4190488746152ce0d80482e1f5553e76149f3e6e730ef85192563f2c11882db9","target":"graph","created_at":"2026-07-05T03:12:47Z","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/2104.01002/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Jupyter notebook allows data scientists to write machine learning code together with its documentation in cells. In this paper, we propose a new task of code documentation generation (CDG) for computational notebooks. In contrast to the previous CDG tasks which focus on generating documentation for single code snippets, in a computational notebook, one documentation in a markdown cell often corresponds to multiple code cells, and these code cells have an inherent structure. We proposed a new model (HAConvGNN) that uses a hierarchical attention mechanism to consider the relevant code cells and ","authors_text":"April Wang, Dakuo Wang, Lingfei Wu, Xuye Liu, Yufang Hou","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2021-03-31T22:36:41Z","title":"HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.01002","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":"sha256:48d0aac156ac83ce98385cc7781c5a6c6b7046d3c0e6a8e923fef79e4efc531d","target":"record","created_at":"2026-07-05T03:12:47Z","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":"aabab9625cd34dcda2af581eb325bae1381a8f019e71f524630746426dd6a9bc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2021-03-31T22:36:41Z","title_canon_sha256":"56a44313e2d394651221434578bd53d0277394faefd6f4b2e6bfc2a7a1cbb6ca"},"schema_version":"1.0","source":{"id":"2104.01002","kind":"arxiv","version":2}},"canonical_sha256":"eda31704ab71acc6d85a766990268023746e83b257b02cf088eb1c04fbe1c4ed","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eda31704ab71acc6d85a766990268023746e83b257b02cf088eb1c04fbe1c4ed","first_computed_at":"2026-07-05T03:12:47.818326Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:12:47.818326Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/pfMuEXezBl14HuF9CHAYe5iWUvjxtdBKNFhBo/zoH/MvLUA9NPSmDnezWqLjlSQKRStWwSpEcYW9JZSCx6DCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:12:47.818806Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.01002","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:48d0aac156ac83ce98385cc7781c5a6c6b7046d3c0e6a8e923fef79e4efc531d","sha256:4190488746152ce0d80482e1f5553e76149f3e6e730ef85192563f2c11882db9"],"state_sha256":"6c3d2f4c86ca074d49aae761383a77f83768d21c808b29db228a8a30e3a022f7"}