{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:W6ITXSVO643KCSN7TC5EEDNME7","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":"c9f5024cf4f972576b14809bce282af9478b59e25d855a581339333394e281a8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-22T05:04:33Z","title_canon_sha256":"0df5b4e15e926fa5bc3dea739180b0cddb75c30a11bcf1d4aff639e7ee1e7547"},"schema_version":"1.0","source":{"id":"2504.15587","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.15587","created_at":"2026-06-04T01:08:28Z"},{"alias_kind":"arxiv_version","alias_value":"2504.15587v2","created_at":"2026-06-04T01:08:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.15587","created_at":"2026-06-04T01:08:28Z"},{"alias_kind":"pith_short_12","alias_value":"W6ITXSVO643K","created_at":"2026-06-04T01:08:28Z"},{"alias_kind":"pith_short_16","alias_value":"W6ITXSVO643KCSN7","created_at":"2026-06-04T01:08:28Z"},{"alias_kind":"pith_short_8","alias_value":"W6ITXSVO","created_at":"2026-06-04T01:08:28Z"}],"graph_snapshots":[{"event_id":"sha256:92834fddb2bfe5d742bb36dd27081f0f764e13d53769d2d0b1c2858fc3a5566f","target":"graph","created_at":"2026-06-04T01:08:28Z","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/2504.15587/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Molecular generation plays an important role in drug discovery and materials science, especially in data-scarce scenarios where traditional generative models often struggle to achieve satisfactory conditional generalization. To address this challenge, we propose MetaMolGen, a first-order meta-learning-based molecular generator designed for few-shot and property-conditioned molecular generation. MetaMolGen standardizes the distribution of graph motifs by mapping them to a normalized latent space, and employs a lightweight autoregressive sequence model to generate SMILES sequences that faithfull","authors_text":"Chang Liu, Jie Zhang, Yiping Song, Yizhen Liu, Zheng Xie, Zimo Yan","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-22T05:04:33Z","title":"MetaMolGen: A Neural Graph Motif Generation Model for De Novo Molecular Design"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.15587","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:ffdd4dd9a8d76599f748596446ccae1ee98101615e8fbd5e831ec3cc3de91f8b","target":"record","created_at":"2026-06-04T01:08:28Z","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":"c9f5024cf4f972576b14809bce282af9478b59e25d855a581339333394e281a8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-22T05:04:33Z","title_canon_sha256":"0df5b4e15e926fa5bc3dea739180b0cddb75c30a11bcf1d4aff639e7ee1e7547"},"schema_version":"1.0","source":{"id":"2504.15587","kind":"arxiv","version":2}},"canonical_sha256":"b7913bcaaef736a149bf98ba420dac27f52f0b030402e271a24ee0c24f99c994","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7913bcaaef736a149bf98ba420dac27f52f0b030402e271a24ee0c24f99c994","first_computed_at":"2026-06-04T01:08:28.821672Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-04T01:08:28.821672Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SezIbyiPPKQE4LZQFVsfkL/r6PDNReBQfgPIfkbPU8cRCwZRGBbtMlg5ULm+z6KRFWJDImz7PdOGRlwNZgJxAg==","signature_status":"signed_v1","signed_at":"2026-06-04T01:08:28.822264Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.15587","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ffdd4dd9a8d76599f748596446ccae1ee98101615e8fbd5e831ec3cc3de91f8b","sha256:92834fddb2bfe5d742bb36dd27081f0f764e13d53769d2d0b1c2858fc3a5566f"],"state_sha256":"2a9961b40a7c22b4f4c11213eb3f396d6ce64f9fc0df86c0710b51c1eba8fc3f"}