{"as_of":"2026-08-16T20:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c416b6aa18bdff9d9b4c298f9182f7b52072df274b9acb1013a525d33615b65d","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T05:27:52.834598Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2504.20770/citation-record","integrity":"/paper/2504.20770/integrity","json":"/paper/2504.20770/citation-record.json","paper":"/paper/2504.20770"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1811.09766","last_updated":"2018-11-24T05:23:39Z","snapshot_observed_at":"2026-08-14T17:54:27.410762Z","submitted_at":"2018-11-24T05:23:39Z","title":"DEFactor: Differentiable Edge Factorization-based Probabilistic Graph Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.09766","snapshot_observed_at":"2026-08-16T05:27:52.476423Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.476423Z"},"links":{"cited_paper":"/paper/1811.09766","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:4b5e8ac56e42efcefda39218564064d913899dbe21e8bf701b84736f8bfa7736","observation_id":"35dfa45b-a0cb-4b61-ab72-0db7c25a6e74","resolution":{"observed_at":"2026-08-16T05:27:52.476423Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.486799Z","title":null,"venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.486799Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:a8e6b52d1d854f316f95ed70530f249f5ba647cf48c422985ec4efdf743bace0","observation_id":"5be043ca-832a-4027-9f64-26b0ab9fdb28","resolution":{"observed_at":"2026-08-16T05:27:52.486799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1805.11973","last_updated":"2022-09-27T10:04:29Z","snapshot_observed_at":"2026-08-14T19:09:29.394743Z","submitted_at":"2018-05-30T13:56:06Z","title":"MolGAN: An implicit generative model for small molecular graphs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.11973","snapshot_observed_at":"2026-08-16T05:27:52.500416Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.500416Z"},"links":{"cited_paper":"/paper/1805.11973","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:bea1fac93f0836a563e73e0f77c9aff985845d1358927510fd94fcb7e5654772","observation_id":"7cc7640c-79ac-4088-96d2-d70b1dcf9cc5","resolution":{"observed_at":"2026-08-16T05:27:52.500416Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.510229Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.510229Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:90ed4eda4dc7aaa3b805736322b7ef418b90f878b3898f85d099b24190ff2e2c","observation_id":"0b85ea3d-f8cd-48a1-9762-88b4b01e1a91","resolution":{"observed_at":"2026-08-16T05:27:52.510229Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-08-14T18:16:28.847993Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-16T05:27:52.519148Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.519148Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:1bae81ee330d9f32133ba778ec249a69f2b63cbe03cd29052d1acc7ad28126f5","observation_id":"9433edd8-14a0-4fe5-98d6-9c7468af9713","resolution":{"observed_at":"2026-08-16T05:27:52.519148Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.525082Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.525082Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:825ce33fa4f20ef1a07c6b935cc06647f5175c6d6b11fdc77ae1bc8757326f13","observation_id":"f654491f-7bd9-480e-944b-13e8d10aa22b","resolution":{"observed_at":"2026-08-16T05:27:52.525082Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1608.04117","last_updated":"2016-09-22T20:14:09Z","snapshot_observed_at":"2026-08-14T21:44:15.221134Z","submitted_at":"2016-08-14T17:10:30Z","title":"The Importance of Skip Connections in Biomedical Image Segmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.04117","snapshot_observed_at":"2026-08-16T05:27:52.533170Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.533170Z"},"links":{"cited_paper":"/paper/1608.04117","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:2895e9a4d85ca1ca1039eaa8b31648d7ad10e90ff227d73e9660300421a3b8e6","observation_id":"5f140447-0a89-4814-9eb1-6aa5fcf25fc8","resolution":{"observed_at":"2026-08-16T05:27:52.533170Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:54.505014Z","title":"Schoenholz, Patrick F","venue":null,"work_id":"f7c43e66-02e6-49ac-92bd-3b65fa87b782","year":2017},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.540843Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:6fd07bb22f2db800940d863ed0621d16b6a326dec88de0228dc2f87710c8bad6","observation_id":"9ef593c4-46a5-4e23-bb3d-ea9de76c411e","resolution":{"observed_at":"2026-08-16T05:27:54.523435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1610.02415","last_updated":"2017-12-05T06:22:03Z","snapshot_observed_at":"2026-08-16T01:04:01.557597Z","submitted_at":"2016-10-07T20:26:34Z","title":"Automatic chemical design using a data-driven continuous representation of molecules","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.02415","snapshot_observed_at":"2026-08-16T05:27:52.549099Z","title":"Hirzel, Ryan P","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.549099Z"},"links":{"cited_paper":"/paper/1610.02415","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:a16d33e00e6b9749640a37143b950a7eb88f3926cd8f4f6f418819761b0b7688","observation_id":"890e07fb-f678-4771-b91b-fe409dd36dc4","resolution":{"observed_at":"2026-08-16T05:27:52.549099Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.562787Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.562787Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:7721a82bc241980c6c928724f5c46b4527ff2fb2557752204196d15ac88e235f","observation_id":"e8aab42c-7baa-4ad5-9dc4-89c66c48bcc2","resolution":{"observed_at":"2026-08-16T05:27:52.562787Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.568674Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.568674Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:94ec4149cfe06347574a4effae1fae81f99993d920b23f3433f736073ac022ec","observation_id":"0d489461-218d-4e68-9f8d-8785312d6b1b","resolution":{"observed_at":"2026-08-16T05:27:52.568674Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:54.423000Z","title":null,"venue":null,"work_id":"4ef8a718-6649-4dd1-b659-37a6d4fa01ce","year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.577031Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:be1cdbe999b769b69f69edce7b694882d6657153d3e732b7883035ffcc57096b","observation_id":"df41c7e0-d5a9-4e1a-a235-9de2a65ce1bc","resolution":{"observed_at":"2026-08-16T05:27:54.434738Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:54.360443Z","title":null,"venue":null,"work_id":"a4a497bb-c5be-40a9-a305-b63d12698fd9","year":2020},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.585996Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:f3372a5759bf4924b750150688fba4fb71a60ce5794f6780fee27fe5b56e770d","observation_id":"49064706-56a9-4be9-9625-b0998760a678","resolution":{"observed_at":"2026-08-16T05:27:54.370568Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18632/oncotarget.14073","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.938241Z","title":null,"venue":null,"work_id":"f4e2514a-ac46-451f-93ad-0893d4bdadce","year":2016},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.592365Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:90f1e9ba94190ee409b8edc8e2b0d2ae0d136ea6375002ce8d1849d18dd76f8a","observation_id":"eeddcadf-366c-4bf5-91bc-329c352c0c09","resolution":{"observed_at":"2026-08-16T05:27:52.951166Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:54.325182Z","title":null,"venue":null,"work_id":"f1aedc74-df08-4460-be14-f09236d8933c","year":2021},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.599724Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:d86546706731b10e41e35790598f9f80d81d977b9e7f502c7f5d61110957ffe4","observation_id":"3ceadd4f-98bb-4bd5-9e8c-c3bbfeb7f8d6","resolution":{"observed_at":"2026-08-16T05:27:54.333068Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.607892Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.607892Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:1fecb6618ed00e7a63879e6c2b40ee89c93c312d798a18b22637eb9cfcf70547","observation_id":"c7fea1ce-39eb-410a-84be-339796a2acae","resolution":{"observed_at":"2026-08-16T05:27:52.607892Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:54.250463Z","title":null,"venue":null,"work_id":"6300553e-e945-4411-8ebc-1cc125bd7958","year":2020},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.616164Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:c7e7b5d0585987af18a0fa878b46e96648d7ea2b898f6a15e1f192fb6afd39aa","observation_id":"19096e95-7476-46fa-bf20-9185169daa28","resolution":{"observed_at":"2026-08-16T05:27:54.263195Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.03324","last_updated":"2018-03-08T22:20:00Z","snapshot_observed_at":"2026-08-14T19:37:59.979230Z","submitted_at":"2018-03-08T22:20:00Z","title":"Learning Deep Generative Models of Graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.03324","snapshot_observed_at":"2026-08-16T05:27:52.627221Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.627221Z"},"links":{"cited_paper":"/paper/1803.03324","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:a759e1e1f2ca23cb415ceb8930de3de14c1b7304269ebfe2b86ce1fc48a91d2f","observation_id":"c798233a-97f8-414f-ad82-be131507de63","resolution":{"observed_at":"2026-08-16T05:27:52.627221Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:54.199962Z","title":null,"venue":null,"work_id":"a951f949-ae03-40fa-b2e1-fa054c4d23b2","year":2023},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.640548Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:f64145a02d8be13d963a13a1d9542a90c675da540d75d82ea4e10973b5d00b5d","observation_id":"e1843167-ae84-402c-967a-f0ea717db619","resolution":{"observed_at":"2026-08-16T05:27:54.207808Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:54.161649Z","title":null,"venue":null,"work_id":"2fd97f69-095f-477d-a426-e24d7ce3fc9d","year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.649418Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:de6b193d379a70fc3392019c78fd1b17a7b19f25d188d51efce46bdf02f1f16c","observation_id":"60849131-8164-4b83-af0e-6a5094852e36","resolution":{"observed_at":"2026-08-16T05:27:54.171671Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:54.124548Z","title":null,"venue":null,"work_id":"f66f0a7a-ebc5-40be-8a1b-171d3f7c54d7","year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.656549Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:042f77e3c7f36d76a7451b33e32631371f4f445d28e42f34a8f21552e6f42812","observation_id":"9e13fd27-f4ff-44d5-943a-2a6b650d32a5","resolution":{"observed_at":"2026-08-16T05:27:54.135876Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.08455","last_updated":"2022-02-17T06:02:06Z","snapshot_observed_at":"2026-08-16T17:20:40.515542Z","submitted_at":"2022-02-17T06:02:06Z","title":"Transformer for Graphs: An Overview from Architecture Perspective","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.08455","snapshot_observed_at":"2026-08-16T05:27:52.672239Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.672239Z"},"links":{"cited_paper":"/paper/2202.08455","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:fbaf21a0b361b4dcb41c6b9155f3447d77d76a7b46693ac55f8ef28dc2ab23e1","observation_id":"a92936b4-8e99-4588-a372-3cc6ea4176fd","resolution":{"observed_at":"2026-08-16T05:27:52.672239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.04345","last_updated":"2021-04-09T13:13:06Z","snapshot_observed_at":"2026-08-16T18:32:46.120267Z","submitted_at":"2021-04-09T13:13:06Z","title":"A Graph VAE and Graph Transformer Approach to Generating Molecular Graphs","version":1},"cited_work":{"arxiv_id":"2104.04345","doi":null,"metadata_source":"pith","pith_arxiv_id":"2104.04345","snapshot_observed_at":"2026-08-16T05:27:53.242747Z","title":"A Graph VAE and Graph Transformer Approach to Generating Molecular Graphs","venue":"cs.LG","work_id":"68e6b0ba-daf6-457b-841c-4ff32a092fcb","year":2021},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.679397Z"},"links":{"cited_paper":"/paper/2104.04345","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:cfb4093004e44f74310d06a64d6e12537af272cfeab6923c38f9da36b8d41474","observation_id":"d46401c3-a076-4716-ba5a-82c08dabbc44","resolution":{"observed_at":"2026-08-16T05:27:53.255685Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.12823","last_updated":"2020-10-28T14:11:16Z","snapshot_observed_at":"2026-08-14T17:51:31.365930Z","submitted_at":"2018-11-29T08:48:20Z","title":"Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.12823","snapshot_observed_at":"2026-08-16T05:27:52.686484Z","title":"Nikolenko, Alán Aspuru-Guzik, and Alex Zhavoronkov","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.686484Z"},"links":{"cited_paper":"/paper/1811.12823","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:e570a061f5bdfdf24c49f741195a7a40402f7ae28faae3c0807f510324e4edc2","observation_id":"b45a1307-2eb3-47d9-b257-f8f706a63192","resolution":{"observed_at":"2026-08-16T05:27:52.686484Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.13372","last_updated":"2019-05-31T01:33:13Z","snapshot_observed_at":"2026-08-15T08:10:48.203226Z","submitted_at":"2019-05-31T01:33:13Z","title":"MolecularRNN: Generating realistic molecular graphs with optimized properties","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.13372","snapshot_observed_at":"2026-08-16T05:27:52.701267Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.701267Z"},"links":{"cited_paper":"/paper/1905.13372","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:96eae970e9ca046c5b409c24d0266e049d5fdb53c08536886087d84e38d60e8c","observation_id":"e230a308-008c-48f0-a7c4-3e9183ff15b9","resolution":{"observed_at":"2026-08-16T05:27:52.701267Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1803.09518","last_updated":"2018-08-01T14:20:53Z","snapshot_observed_at":"2026-08-14T19:32:31.153143Z","submitted_at":"2018-03-26T11:36:24Z","title":"Fr\\'echet ChemNet Distance: A metric for generative models for molecules in drug discovery","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.09518","snapshot_observed_at":"2026-08-16T05:27:52.719354Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.719354Z"},"links":{"cited_paper":"/paper/1803.09518","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:ae9bf690b5ea24088d5b5f17dfae97c05d8fe08d032bacce31bbd5a0eeb97225","observation_id":"33e64615-5b43-4560-a5d4-bc2af1f76ac9","resolution":{"observed_at":"2026-08-16T05:27:52.719354Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.26434/chemrxiv.8299544","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.897211Z","title":null,"venue":null,"work_id":"1f127247-f33d-4868-90b1-eec736864153","year":2019},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.727382Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:456037c9ea95bf3e3f9a153db49f8c0be6b38218ea1788624a7ef01198fb1ee2","observation_id":"d345a31b-bb18-46b0-9b88-68f057136ebf","resolution":{"observed_at":"2026-08-16T05:27:52.908533Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:54.076823Z","title":null,"venue":null,"work_id":"7898aa1f-2624-44a8-9612-5ccb2421d2d5","year":2014},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.737115Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:f6b8ff5d5f134be37c4985682a0ad8ff604cb67bad394b0ed5ca6cefc8dd8f9f","observation_id":"5cb5801f-da3a-4fa5-a991-eb3e2a753f62","resolution":{"observed_at":"2026-08-16T05:27:54.087298Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.748989Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.748989Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:97cfc087b231d90f6162b289a4094a69f62cefefb36c1d31329e3ab2d366d690","observation_id":"326a0d83-89ad-4392-8e17-435838006ff2","resolution":{"observed_at":"2026-08-16T05:27:52.748989Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1505.04597","last_updated":"2015-05-18T11:28:37Z","snapshot_observed_at":"2026-08-15T21:30:31.645090Z","submitted_at":"2015-05-18T11:28:37Z","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1505.04597","snapshot_observed_at":"2026-08-16T05:27:52.755722Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.755722Z"},"links":{"cited_paper":"/paper/1505.04597","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:7866939f4ba20f8317b9cdf1aedbfe1fbd123658a7ff3bd0af1184c0209ad5d7","observation_id":"5bcd0083-38d6-4209-bbe6-9479d7de64c0","resolution":{"observed_at":"2026-08-16T05:27:52.755722Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1701.01329","last_updated":"2017-01-05T14:28:34Z","snapshot_observed_at":"2026-08-14T21:22:26.809417Z","submitted_at":"2017-01-05T14:28:34Z","title":"Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks","version":1},"cited_work":{"arxiv_id":"1701.01329","doi":null,"metadata_source":"pith","pith_arxiv_id":"1701.01329","snapshot_observed_at":"2026-08-16T05:27:53.019384Z","title":"Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks","venue":"cs.NE","work_id":"736b792c-72a2-4d7c-a9c3-ee214791fffc","year":2017},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.762313Z"},"links":{"cited_paper":"/paper/1701.01329","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:452e23cd97ad0724a724118a320125b63b62ad6a14612c5e379f530ae0b78b82","observation_id":"2ed7dcf0-e253-44b1-a724-d05fe2aacfb2","resolution":{"observed_at":"2026-08-16T05:27:53.035736Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02502","last_updated":"2022-10-05T20:19:21Z","snapshot_observed_at":"2026-08-11T15:38:14.931716Z","submitted_at":"2020-10-06T06:15:51Z","title":"Denoising Diffusion Implicit Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02502","snapshot_observed_at":"2026-08-16T05:27:52.770163Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.770163Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:8aea10f4dfed32ba4d18be5982e4801c2a5cca7636af08590c435aae4ad2437e","observation_id":"7d1d01f8-044b-429b-a692-5efccb1319f2","resolution":{"observed_at":"2026-08-16T05:27:52.770163Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.798264Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.798264Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:88eec591ef0f37e8b6af8c4633b3b1f218bd3a24bb5bd5e77123c12ca9d878bd","observation_id":"63add16d-d7c7-4dca-bcf9-e65e3af80fb0","resolution":{"observed_at":"2026-08-16T05:27:52.798264Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.807728Z","title":null,"venue":null,"work_id":null,"year":1988},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.807728Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:93348ef97bea636e49cc20e808e0ec98f9cd5974495e0ede6c4eb4843cad2cbc","observation_id":"f45f7d3f-27fa-489d-866d-5db560f433ed","resolution":{"observed_at":"2026-08-16T05:27:52.807728Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.814781Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.814781Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:b1b1d40b33914fee1d70f2d773a2b5842a86a89280eb6e0fb47f86301e67c7f1","observation_id":"2aa4fc41-3959-4229-bc58-3a976f2d7bdf","resolution":{"observed_at":"2026-08-16T05:27:52.814781Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:52.820796Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.820796Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:8b5e2819a797911f9c56f87042ef133badb1bcf2d59b3a7ce0cd889b86b1fb82","observation_id":"ec946dbf-f10c-4d5f-9f4e-97569e429e00","resolution":{"observed_at":"2026-08-16T05:27:52.820796Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:53.877433Z","title":null,"venue":null,"work_id":"5dd4bc47-adb3-404b-a694-9121303338ca","year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.827848Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:cbb98fa035c14af6bd47c8fd509b824a893eada233b37a8d6c16c7cfffc7a696","observation_id":"033f4fbe-383e-4e9f-ae55-e8c06d5aef2b","resolution":{"observed_at":"2026-08-16T05:27:53.888577Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:27:53.848612Z","title":null,"venue":null,"work_id":"636b5228-90b3-4371-828d-15e46b7f5345","year":2018},"citing_paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T05:27:52.834598Z"},"links":{"citing_paper":"/paper/2504.20770"},"observation_digest":"sha256:2ddd617d51ec47959fb86bd542d595e08ddf6bf3bd1d249e7a612f55206b5930","observation_id":"fe992cc9-2f2a-4435-b875-8eeda6127764","resolution":{"observed_at":"2026-08-16T05:27:53.857519Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.20770","last_updated":"2025-04-29T13:51:07Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T05:17:59.399645Z","submitted_at":"2025-04-29T13:51:07Z","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":33,"verified_exact":4,"verified_fuzzy":1},"total_outbound_references":38},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2504.20770."}