{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:KMMQ7NB6XKAWO22P53SZBOQOKZ","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":"76e5a7243f3e9d62046c374d8336485e359406dc27dc085bf95ededffd9558f7","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.BM","submitted_at":"2022-12-17T09:09:23Z","title_canon_sha256":"806070f1a08d56fed11be1ee414942e04babd2c2b5706a2e5fea28119a1b8965"},"schema_version":"1.0","source":{"id":"2212.08826","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.08826","created_at":"2026-07-05T05:26:14Z"},{"alias_kind":"arxiv_version","alias_value":"2212.08826v1","created_at":"2026-07-05T05:26:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.08826","created_at":"2026-07-05T05:26:14Z"},{"alias_kind":"pith_short_12","alias_value":"KMMQ7NB6XKAW","created_at":"2026-07-05T05:26:14Z"},{"alias_kind":"pith_short_16","alias_value":"KMMQ7NB6XKAWO22P","created_at":"2026-07-05T05:26:14Z"},{"alias_kind":"pith_short_8","alias_value":"KMMQ7NB6","created_at":"2026-07-05T05:26:14Z"}],"graph_snapshots":[{"event_id":"sha256:f51978bd46a86080a111fe6b1d91df41c3b61e3acf7b6516819b1c494754510f","target":"graph","created_at":"2026-07-05T05:26:14Z","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/2212.08826/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning methods have been used to accelerate the molecule optimization process. However, efficient search for optimized molecules satisfying several properties with scarce labeled data remains a challenge for machine learning molecule optimization. In this study, we propose MOMO, a multi-objective molecule optimization framework to address the challenge by combining learning of chemical knowledge with Pareto-based multi-objective evolutionary search. To learn chemistry, it employs a self-supervised codec to construct an implicit chemical space and acquire the continues representation ","authors_text":"Chunhou Zheng, Xiangxiang Zeng, Xin Xia, Yansen Su","cross_cats":["cs.LG","cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.BM","submitted_at":"2022-12-17T09:09:23Z","title":"Molecule optimization via multi-objective evolutionary in implicit chemical space"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.08826","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":"sha256:0c2d49b3c5a36c4695583bb3df3324fce100f6805394c056d42014e536a1fd6c","target":"record","created_at":"2026-07-05T05:26:14Z","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":"76e5a7243f3e9d62046c374d8336485e359406dc27dc085bf95ededffd9558f7","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.BM","submitted_at":"2022-12-17T09:09:23Z","title_canon_sha256":"806070f1a08d56fed11be1ee414942e04babd2c2b5706a2e5fea28119a1b8965"},"schema_version":"1.0","source":{"id":"2212.08826","kind":"arxiv","version":1}},"canonical_sha256":"53190fb43eba81676b4feee590ba0e565de795a2e8179f5f4ed3a1bde515d6a9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"53190fb43eba81676b4feee590ba0e565de795a2e8179f5f4ed3a1bde515d6a9","first_computed_at":"2026-07-05T05:26:14.744051Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:26:14.744051Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"D+dArDkTKrzOtAaNjqEI+Z2Wni1tE+1NynhYLCIXUQCtWzHx53qIFWNxDc2yc2i2ez1D7OcsMA1qPj5wcpx+Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:26:14.744395Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.08826","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0c2d49b3c5a36c4695583bb3df3324fce100f6805394c056d42014e536a1fd6c","sha256:f51978bd46a86080a111fe6b1d91df41c3b61e3acf7b6516819b1c494754510f"],"state_sha256":"eba463e98bcd163b9cabd394bd7f5032b67f8b69d335614ae4e7facf089e41c8"}