{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:QR7M5TURRADS5IQ23HELP46EDG","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":"9e9a9148ab71313fa2d7217cc0b7ee03c27d0563a8e857e3a84a804da7288400","cross_cats_sorted":["q-bio.BM"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-10-17T05:03:35Z","title_canon_sha256":"9bfa8016eacf5ef5c324625434ed88535a45f3624a4d818037594ba00532839e"},"schema_version":"1.0","source":{"id":"2210.08749","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.08749","created_at":"2026-07-05T05:09:23Z"},{"alias_kind":"arxiv_version","alias_value":"2210.08749v2","created_at":"2026-07-05T05:09:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.08749","created_at":"2026-07-05T05:09:23Z"},{"alias_kind":"pith_short_12","alias_value":"QR7M5TURRADS","created_at":"2026-07-05T05:09:23Z"},{"alias_kind":"pith_short_16","alias_value":"QR7M5TURRADS5IQ2","created_at":"2026-07-05T05:09:23Z"},{"alias_kind":"pith_short_8","alias_value":"QR7M5TUR","created_at":"2026-07-05T05:09:23Z"}],"graph_snapshots":[{"event_id":"sha256:1a8b5ce933c534de6b1395d693e98b58b11d5c6d5b9f5a2266491ae22750dd6e","target":"graph","created_at":"2026-07-05T05:09:23Z","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/2210.08749/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In the scope of drug discovery, the molecular design aims to identify novel compounds from the chemical space where the potential drug-like molecules are estimated to be in the order of 10^60 - 10^100. Since this search task is computationally intractable due to the unbounded search space, deep learning draws a lot of attention as a new way of generating unseen molecules. As we seek compounds with specific target proteins, we propose a Transformer-based deep model for de novo target-specific molecular design. The proposed method is capable of generating both drug-like compounds (without specif","authors_text":"Honggang Zhao, Simone Sciabola, Wenlu Wang, Ye Wang","cross_cats":["q-bio.BM"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-10-17T05:03:35Z","title":"A Transformer-based Generative Model for De Novo Molecular Design"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.08749","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":"sha256:0e3528b643f28a8454c9b550054fea929a71896cfdcfff139c2deafa14374df2","target":"record","created_at":"2026-07-05T05:09:23Z","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":"9e9a9148ab71313fa2d7217cc0b7ee03c27d0563a8e857e3a84a804da7288400","cross_cats_sorted":["q-bio.BM"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-10-17T05:03:35Z","title_canon_sha256":"9bfa8016eacf5ef5c324625434ed88535a45f3624a4d818037594ba00532839e"},"schema_version":"1.0","source":{"id":"2210.08749","kind":"arxiv","version":2}},"canonical_sha256":"847ecece9188072ea21ad9c8b7f3c419a15acee9e99dad7cec8842c7b9729741","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"847ecece9188072ea21ad9c8b7f3c419a15acee9e99dad7cec8842c7b9729741","first_computed_at":"2026-07-05T05:09:23.309537Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:09:23.309537Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LgaeXmJU/rjHqrSxHcTM8Yhe33O5rRrc8YzwShwJyOOW58nQCgUi5IGsN8nlphGREKpPCn2KKwGGyc3jeCLfBw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:09:23.310046Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.08749","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0e3528b643f28a8454c9b550054fea929a71896cfdcfff139c2deafa14374df2","sha256:1a8b5ce933c534de6b1395d693e98b58b11d5c6d5b9f5a2266491ae22750dd6e"],"state_sha256":"61a8f4b577d9e4824809b51e17507e6a495d8149285b298719515af2e5318729"}