{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:7FMOFOPWXCEPKMGWKLLNUACYT3","short_pith_number":"pith:7FMOFOPW","canonical_record":{"source":{"id":"1811.06837","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2018-11-14T14:45:35Z","cross_cats_sorted":["cs.SE","stat.ML"],"title_canon_sha256":"a58a615c23aa21f323ab7399356216c77f8891de934356a3e7bab533c18ba146","abstract_canon_sha256":"6f3d7616f5e094b6d92ee4161967ad230c9745fc79456513a97aafb510760495"},"schema_version":"1.0"},"canonical_sha256":"f958e2b9f6b888f530d652d6da00589ef499e93e28cc3340eaf6b5ed23197f51","source":{"kind":"arxiv","id":"1811.06837","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.06837","created_at":"2026-05-18T00:00:33Z"},{"alias_kind":"arxiv_version","alias_value":"1811.06837v1","created_at":"2026-05-18T00:00:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.06837","created_at":"2026-05-18T00:00:33Z"},{"alias_kind":"pith_short_12","alias_value":"7FMOFOPWXCEP","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"7FMOFOPWXCEPKMGW","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"7FMOFOPW","created_at":"2026-05-18T12:32:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:7FMOFOPWXCEPKMGWKLLNUACYT3","target":"record","payload":{"canonical_record":{"source":{"id":"1811.06837","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2018-11-14T14:45:35Z","cross_cats_sorted":["cs.SE","stat.ML"],"title_canon_sha256":"a58a615c23aa21f323ab7399356216c77f8891de934356a3e7bab533c18ba146","abstract_canon_sha256":"6f3d7616f5e094b6d92ee4161967ad230c9745fc79456513a97aafb510760495"},"schema_version":"1.0"},"canonical_sha256":"f958e2b9f6b888f530d652d6da00589ef499e93e28cc3340eaf6b5ed23197f51","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:33.747928Z","signature_b64":"eu6hdforVFWUmA9o3XG5GuAn9pOrTn0/NIXcmEFi9XJ43SnjkmyTpQ5AWvv3g1paHUFt0KqkEvSCSOcMZYc4CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f958e2b9f6b888f530d652d6da00589ef499e93e28cc3340eaf6b5ed23197f51","last_reissued_at":"2026-05-18T00:00:33.747397Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:33.747397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.06837","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:00:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p5zIuKgjLzoveT/WolJOanJpKkurlFfXGWKwz36ZtoKX45agrJH4UISoQh8BW82bD4sdtU1s1j3+NjSOW2K1Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T20:35:51.410938Z"},"content_sha256":"dbdd07f9ab9584baf628e95cd8d3a95084741189a8480aa9cb0d2c075c838815","schema_version":"1.0","event_id":"sha256:dbdd07f9ab9584baf628e95cd8d3a95084741189a8480aa9cb0d2c075c838815"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:7FMOFOPWXCEPKMGWKLLNUACYT3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Grammar-Based Structural CNN Decoder for Code Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SE","stat.ML"],"primary_cat":"cs.LG","authors_text":"Ge Li, Lili Mou, Lu Zhang, Qihao Zhu, Yingfei Xiong, Zeyu Sun","submitted_at":"2018-11-14T14:45:35Z","abstract_excerpt":"Code generation maps a program description to executable source code in a programming language. Existing approaches mainly rely on a recurrent neural network (RNN) as the decoder. However, we find that a program contains significantly more tokens than a natural language sentence, and thus it may be inappropriate for RNN to capture such a long sequence. In this paper, we propose a grammar-based structural convolutional neural network (CNN) for code generation. Our model generates a program by predicting the grammar rules of the programming language; we design several CNN modules, including the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.06837","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-18T00:00:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3R8n39EnPau1Wxsq6J8iZcBlSFuqsX7IHjN4mdrYkSI7vGzVtZ/u4B1MldybNG/wMoCXNLVSppTUTlU79mBwBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T20:35:51.411290Z"},"content_sha256":"0bf766f333fd96cf0177b2ba464fa92ebe139eddf56ae2a25802c7e4a2148eb3","schema_version":"1.0","event_id":"sha256:0bf766f333fd96cf0177b2ba464fa92ebe139eddf56ae2a25802c7e4a2148eb3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7FMOFOPWXCEPKMGWKLLNUACYT3/bundle.json","state_url":"https://pith.science/pith/7FMOFOPWXCEPKMGWKLLNUACYT3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7FMOFOPWXCEPKMGWKLLNUACYT3/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":"2026-06-10T20:35:51Z","links":{"resolver":"https://pith.science/pith/7FMOFOPWXCEPKMGWKLLNUACYT3","bundle":"https://pith.science/pith/7FMOFOPWXCEPKMGWKLLNUACYT3/bundle.json","state":"https://pith.science/pith/7FMOFOPWXCEPKMGWKLLNUACYT3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7FMOFOPWXCEPKMGWKLLNUACYT3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:7FMOFOPWXCEPKMGWKLLNUACYT3","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":"6f3d7616f5e094b6d92ee4161967ad230c9745fc79456513a97aafb510760495","cross_cats_sorted":["cs.SE","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2018-11-14T14:45:35Z","title_canon_sha256":"a58a615c23aa21f323ab7399356216c77f8891de934356a3e7bab533c18ba146"},"schema_version":"1.0","source":{"id":"1811.06837","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.06837","created_at":"2026-05-18T00:00:33Z"},{"alias_kind":"arxiv_version","alias_value":"1811.06837v1","created_at":"2026-05-18T00:00:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.06837","created_at":"2026-05-18T00:00:33Z"},{"alias_kind":"pith_short_12","alias_value":"7FMOFOPWXCEP","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"7FMOFOPWXCEPKMGW","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"7FMOFOPW","created_at":"2026-05-18T12:32:11Z"}],"graph_snapshots":[{"event_id":"sha256:0bf766f333fd96cf0177b2ba464fa92ebe139eddf56ae2a25802c7e4a2148eb3","target":"graph","created_at":"2026-05-18T00:00:33Z","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"},"paper":{"abstract_excerpt":"Code generation maps a program description to executable source code in a programming language. Existing approaches mainly rely on a recurrent neural network (RNN) as the decoder. However, we find that a program contains significantly more tokens than a natural language sentence, and thus it may be inappropriate for RNN to capture such a long sequence. In this paper, we propose a grammar-based structural convolutional neural network (CNN) for code generation. Our model generates a program by predicting the grammar rules of the programming language; we design several CNN modules, including the ","authors_text":"Ge Li, Lili Mou, Lu Zhang, Qihao Zhu, Yingfei Xiong, Zeyu Sun","cross_cats":["cs.SE","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2018-11-14T14:45:35Z","title":"A Grammar-Based Structural CNN Decoder for Code Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.06837","kind":"arxiv","version":1},"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:dbdd07f9ab9584baf628e95cd8d3a95084741189a8480aa9cb0d2c075c838815","target":"record","created_at":"2026-05-18T00:00:33Z","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":"6f3d7616f5e094b6d92ee4161967ad230c9745fc79456513a97aafb510760495","cross_cats_sorted":["cs.SE","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2018-11-14T14:45:35Z","title_canon_sha256":"a58a615c23aa21f323ab7399356216c77f8891de934356a3e7bab533c18ba146"},"schema_version":"1.0","source":{"id":"1811.06837","kind":"arxiv","version":1}},"canonical_sha256":"f958e2b9f6b888f530d652d6da00589ef499e93e28cc3340eaf6b5ed23197f51","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f958e2b9f6b888f530d652d6da00589ef499e93e28cc3340eaf6b5ed23197f51","first_computed_at":"2026-05-18T00:00:33.747397Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:00:33.747397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eu6hdforVFWUmA9o3XG5GuAn9pOrTn0/NIXcmEFi9XJ43SnjkmyTpQ5AWvv3g1paHUFt0KqkEvSCSOcMZYc4CQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:00:33.747928Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.06837","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dbdd07f9ab9584baf628e95cd8d3a95084741189a8480aa9cb0d2c075c838815","sha256:0bf766f333fd96cf0177b2ba464fa92ebe139eddf56ae2a25802c7e4a2148eb3"],"state_sha256":"7cc0330c26fc19927719f11705db0ccb40f54e2ea7e1710e9fb70b4806c7d67e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C0vlUxvZQSOzako/kWCqVlKbU3yWq6Is05rMnvCKsqL8zriE5X+ZzWmlIV+7x8Psf/XgcszGZe0iuVaRJmKFAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T20:35:51.413224Z","bundle_sha256":"4cadb415caf90074f27653f38fb1b1ffc1303030e15cd6771e94cd9203396a2e"}}