{"as_of":"2026-08-19T11:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a29981a2edac465c2834b462a10cb3f3ec9ec015e032b4568ffcb6dae7a8ab90","coverage":[{"denominator":58,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":58,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T15:20:02.936388Z","state":"measured"},{"denominator":58,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":58,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+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/2608.01007/citation-record","integrity":"/paper/2608.01007/integrity","json":"/paper/2608.01007/citation-record.json","paper":"/paper/2608.01007"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:20:04.063878Z","title":"Protein modeling and structure-based drug design,","venue":null,"work_id":"d2f72b10-06a7-4a14-815f-e0467235b510","year":2025},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.542070Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:a5d419f5d68c11bb29414b1e9e83295beb2ee8f0dd92f907c799c90ec8faf662","observation_id":"816cdd33-e42a-4587-83f0-514c7e7a7d1a","resolution":{"observed_at":"2026-08-15T15:20:04.068733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:04.048153Z","title":"Geometric deep learning methods and applications in 3d structure-based drug design,","venue":null,"work_id":"2031699a-1135-4b5f-9653-8c833a700026","year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.547825Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:fd1602d09e6b0cf75260e03fbeb66b52ef4727840934873240ebba1474fba678","observation_id":"fd1d9292-6efc-451c-8ff3-4e3c5057d861","resolution":{"observed_at":"2026-08-15T15:20:04.053107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:04.032847Z","title":"From magic bullets to designed multiple ligands,","venue":null,"work_id":"0eb75222-b604-4ed1-9ade-032c1f1e1ef6","year":2004},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.553588Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:208476d307af061f8f41dbf4cb4c371a904c65f42190e13116593a5e9471af86","observation_id":"4c38ae7f-fd66-4257-b27d-d913f1875311","resolution":{"observed_at":"2026-08-15T15:20:04.037881Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:04.017378Z","title":"Multitarget drug discovery and polypharmacology,","venue":null,"work_id":"4be25084-d17d-468a-944c-4df267204a27","year":2016},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.558855Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:e500227cc0982fe2f2dcc0d8f3ada86a0ca9898e7743a396dc46932a885432f3","observation_id":"247d98b5-0039-41f6-999d-5255960867f2","resolution":{"observed_at":"2026-08-15T15:20:04.021929Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:04.001898Z","title":"Computational polypharmacology: a new paradigm for drug discovery,","venue":null,"work_id":"9f0c4bae-4cad-4889-ab29-cd926c5bbec3","year":2017},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.564359Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:0fa35051a8c7fd2b601b764e5c49ad9b308c815bc24486684cf8032943df4d46","observation_id":"64245cbd-4149-4935-8b3c-b5a414cad261","resolution":{"observed_at":"2026-08-15T15:20:04.006908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.984819Z","title":"De novo generation of multi-target compounds using deep generative chemistry,","venue":null,"work_id":"b062373c-35bf-4b7c-ae3d-9562e7022a50","year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.569468Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:c14e1830434e1b435b9e1b0a0d9195d51c4b09f63ddaa7e9fb14cb1b2e2bb3ea","observation_id":"5af5829e-411d-4589-b810-d5479245e793","resolution":{"observed_at":"2026-08-15T15:20:03.990160Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.968638Z","title":"Architecture of the human regulatory network derived from encode data,","venue":null,"work_id":"31433b0f-152c-4d70-9636-58b26a0825d8","year":2012},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.574787Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:1e6a2d21aaffe2c12f8f3dd39fa4959d03a8e95a00ad4207a6453fdeb8ab5652","observation_id":"a42c9361-af79-4e51-bbdf-3f2cc840395d","resolution":{"observed_at":"2026-08-15T15:20:03.973666Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.953283Z","title":"Ligbuilder v3: a multi-target de novo drug design approach,","venue":null,"work_id":"9a0ac48d-02e7-4c72-a5ef-03aa2235d5b1","year":2020},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.580014Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:808d004946a581c7bd7354c91ff05f20be9aba2d991208921a675aab4105d71b","observation_id":"08621652-191b-4a58-9bc4-332ce8368d9d","resolution":{"observed_at":"2026-08-15T15:20:03.958256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.937551Z","title":"Polypharmacology in a single drug: multitarget drugs,","venue":null,"work_id":"d0436399-317a-4eb4-bdab-84fc7fe6d43e","year":2013},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.584547Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:e4591b1b8fb2df74533dc50968fad01ae14e40a40c46719a5b769d3ae4c66011","observation_id":"a91752a2-7092-4021-bf54-40075c9be19f","resolution":{"observed_at":"2026-08-15T15:20:03.942224Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.922337Z","title":"A perspec- tive on multi-target drug discovery and design for complex diseases,","venue":null,"work_id":"bac67675-189e-4e49-a44f-c438433be244","year":2018},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.589120Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:94595e252c167714f652723d555dd764cb7870d6c64ee26bbdc5dd51a8ca8992","observation_id":"52736077-78c2-4a70-8726-d083e2e3dfaa","resolution":{"observed_at":"2026-08-15T15:20:03.926659Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.907478Z","title":"Combination therapeutics in complex diseases,","venue":null,"work_id":"ed23bfcf-6548-44fb-9476-31571ad21cd1","year":2016},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.593938Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:bf2657c4adabbef75e6baacb1feb0cd264c265aa871c7a588df97d82fedf98dc","observation_id":"dbc999bf-9f8d-4b1a-876d-c5b79c701a2c","resolution":{"observed_at":"2026-08-15T15:20:03.911756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.892015Z","title":"Generation of dual-target compounds using a transformer chemical language model,","venue":null,"work_id":"d784d227-9a5c-42f9-8bde-5340f7867ab6","year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.598377Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:f55a617578f3fd8acc634174d514a1a9e73f0c211410b6dada3ac904afcb72c1","observation_id":"fd413c40-c264-4dea-abbb-44299b4b4433","resolution":{"observed_at":"2026-08-15T15:20:03.896804Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.874942Z","title":"Therapeutic strategies of dual-target small molecules to overcome drug resistance in cancer therapy,","venue":null,"work_id":"e8e7031a-259f-490d-903f-3ff18da02f42","year":2023},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.602576Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:9664f6cc656552530e913c21a36ca2d3996c61f4e8784395c564ca326cbccaf7","observation_id":"c29c6050-e56f-41a4-a8ba-5ae3f3dc9bbc","resolution":{"observed_at":"2026-08-15T15:20:03.880203Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.858956Z","title":"Beyond purinergic signaling: Dual ligand approaches to multitarget drug discovery,","venue":null,"work_id":"5856afea-bd29-49a3-9c65-5a11b7e85579","year":2025},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.606636Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:9f23f1bc1b14a6f4e924c5314b0f70c7d7308d59aa5c5ae10690f4213b13cd8d","observation_id":"5e124517-778c-4c9d-8680-be231da5e681","resolution":{"observed_at":"2026-08-15T15:20:03.863865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.841368Z","title":"A 3d generative model for structure-based drug design,","venue":null,"work_id":"871f457d-00aa-4a70-95d3-f49eb42ca9b1","year":2021},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.610667Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:d2eb8c535df6c4ba6db803c5b2f1d84d23c96d83744ff53b2bdf7f7d83d94ec5","observation_id":"9a62dc43-4e7d-438a-a89b-d76fa6ba1a86","resolution":{"observed_at":"2026-08-15T15:20:03.847548Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.825212Z","title":"Pocket2mol: Efficient molecular sampling based on 3d protein pockets,","venue":null,"work_id":"f0c84e93-cf01-4541-a22c-ebab37bb2be7","year":2022},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.615376Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:85fe904a60b157e8e4fba1bb05bd7eac38277bb3ad3aaf890bffa9ca93c3e49b","observation_id":"8fa5a716-dfc6-47bd-a958-e1227a1d3b8d","resolution":{"observed_at":"2026-08-15T15:20:03.830364Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.03543","last_updated":"2023-03-06T23:01:43Z","snapshot_observed_at":"2026-08-16T15:50:18.551454Z","submitted_at":"2023-03-06T23:01:43Z","title":"3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.03543","snapshot_observed_at":"2026-08-15T15:20:02.619523Z","title":"3d equivariant diffusion for target- aware molecule generation and affinity prediction,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.619523Z"},"links":{"cited_paper":"/paper/2303.03543","citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:527ce3351ce3f38873e9835d563c46a73cd2916ab8ed62adf57383b5e2b28820","observation_id":"1b9b018b-cae5-4c40-9351-59c5b3599f53","resolution":{"observed_at":"2026-08-15T15:20:02.619523Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.07902","last_updated":"2024-02-26T05:21:21Z","snapshot_observed_at":"2026-08-18T18:13:30.316546Z","submitted_at":"2024-02-26T05:21:21Z","title":"DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.07902","snapshot_observed_at":"2026-08-15T15:20:02.624110Z","title":"Decompdiff: diffusion models with decomposed priors for structure-based drug design,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.624110Z"},"links":{"cited_paper":"/paper/2403.07902","citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:08024d3d628ad8043b80966faefd072578004a83a0e91361ea76bc2d44c9fd08","observation_id":"2bcf4dbe-7ce7-4481-982e-ea982df7cffc","resolution":{"observed_at":"2026-08-15T15:20:02.624110Z","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":"2026-08-15T15:20:03.808001Z","title":"Kgdiff: towards explainable target-aware molecule generation with knowledge guidance,","venue":null,"work_id":"a59644ae-3481-4006-a074-e4e6a2133ce5","year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.628958Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:307b605f08416ef18bccd39ea3672682f6f997b937f9903554d721df5c71380d","observation_id":"ce84c2db-e8e0-4f77-932c-5fc130db2f87","resolution":{"observed_at":"2026-08-15T15:20:03.813903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.790599Z","title":"Aligning target-aware molecule diffusion models with exact energy optimization,","venue":null,"work_id":"1c0f8810-391e-44da-a958-c794941ec8be","year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.633644Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:f8ee4c1b4ef30b6cf630b64f870d165401629ac1b9952c47166390c9312d7bae","observation_id":"8b50db31-3d98-4cf0-8d92-62c67dd5c4d7","resolution":{"observed_at":"2026-08-15T15:20:03.795593Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.774516Z","title":"Protein-ligand interaction prior for binding-aware 3d molecule diffusion models,","venue":null,"work_id":"457edd25-0dd7-4d16-9457-9d7736ebd112","year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.638216Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:de914b2e59a094a5ea0ee9ff246a35552ca88b31fcd3a6e151bb868e2735c1f9","observation_id":"68cf8bd9-6842-4b49-b77b-35591a67b91c","resolution":{"observed_at":"2026-08-15T15:20:03.779688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12141","last_updated":"2024-05-28T03:48:38Z","snapshot_observed_at":"2026-08-16T13:59:46.597335Z","submitted_at":"2024-04-18T12:43:39Z","title":"MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12141","snapshot_observed_at":"2026-08-15T15:20:02.642943Z","title":"Molcraft: Structure-based drug design in continuous parameter space,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.642943Z"},"links":{"cited_paper":"/paper/2404.12141","citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:76b999ded19cae9fab0725f5eff6f9944a2c9b11e9d584fee486b564fa318660","observation_id":"112c04a0-e752-4bca-b13e-9ab5bb989c70","resolution":{"observed_at":"2026-08-15T15:20:02.642943Z","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":"2026-08-15T15:20:03.757269Z","title":"Multi-objective structure-based drug design using causal discovery,","venue":null,"work_id":"a0f3517f-7dc0-4d4c-b2bf-41f53e1186a9","year":2025},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.648003Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:ab8347bc8805157eca99ccb6e79241451b3994fb037837614baeb65ed50c7f59","observation_id":"d106fd5f-1735-448d-8bf8-1488f14ad812","resolution":{"observed_at":"2026-08-15T15:20:03.762792Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:02.652810Z","title":"Prior-guided flow matching for target-aware molecule design with learnable atom number,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.652810Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:51d2502757484eec719074202ff3fdd477ba2c56a6ea177ac97a0dacb73490ea","observation_id":"5d511713-057e-40f6-8d7e-cf9d8ff5a534","resolution":{"observed_at":"2026-08-15T15:20:02.652810Z","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":"2026-08-15T15:20:03.741036Z","title":"Automated design of multi-target ligands by generative deep learning,","venue":null,"work_id":"84ea8eff-54ba-4da7-9ee2-ae28f8a9bdcd","year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.657461Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:fc95d40b778e1fda5f02806075b044ab9a41861c90223b0afb0d02a3d4de24bc","observation_id":"88586f60-00c9-4321-af66-8bc4bac34c97","resolution":{"observed_at":"2026-08-15T15:20:03.746100Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.725065Z","title":"Reprogramming pretrained target-specific diffusion models for dual-target drug design,","venue":null,"work_id":"d9c979b4-45be-4ef4-847e-6f268654eda6","year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.662384Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:6c108a25c54562bef6f2d678fc8030aa284faa3da8866bf4bd4c82d3a7dc005c","observation_id":"9d497569-a670-4129-b350-e8594ed0ca55","resolution":{"observed_at":"2026-08-15T15:20:03.730246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.07037","last_updated":"2025-03-11T08:07:39Z","snapshot_observed_at":"2026-08-16T15:08:42.054500Z","submitted_at":"2023-08-14T09:56:35Z","title":"Bayesian Flow Networks","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.07037","snapshot_observed_at":"2026-08-15T15:20:02.666984Z","title":"Bayesian flow networks,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.666984Z"},"links":{"cited_paper":"/paper/2308.07037","citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:860ef84df9fb621d5541a96a04eb4b3faf46279d1906cf84226c23d338ae6ca9","observation_id":"9e2fde6e-5ba6-41b8-88e2-5dc8ada298f3","resolution":{"observed_at":"2026-08-15T15:20:02.666984Z","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":"2026-08-15T15:20:02.672317Z","title":"Training products of experts by minimizing contrastive divergence,","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.672317Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:3cd83d1c39a2aa10630816ea150c372fdd07800183770cc0911dc30a6f08e79b","observation_id":"4d4f5313-22fb-49f4-9db0-a9682c8a52e5","resolution":{"observed_at":"2026-08-15T15:20:02.672317Z","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":"2026-08-15T15:20:03.699261Z","title":"Generating 3d molecules conditional on receptor binding sites with deep generative models,","venue":null,"work_id":"fbe7ab9e-f952-4316-9f18-b3f1f0dac5e5","year":2022},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.677227Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:b6e620ba6ab1f9a227c6e1afa5fdef98dc3c2852a204dbd64fedc0d0e067c07f","observation_id":"50a7805b-2ce8-4ca5-902b-45079c28e59c","resolution":{"observed_at":"2026-08-15T15:20:03.703767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.684614Z","title":"Generating 3d molecules for target protein binding,","venue":null,"work_id":"e8e1fe09-412c-4820-8096-6044b2b2735e","year":2022},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.682206Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:1b2ebb3190c67f867ed332d5d6e6c17e9ad69e9a01410984ef78f888f5998f46","observation_id":"ae4b57c6-20e6-4559-b3ac-243e7e76ed26","resolution":{"observed_at":"2026-08-15T15:20:03.689145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.670437Z","title":"Molecule generation for target protein binding with structural motifs,","venue":null,"work_id":"678351f6-5a5b-49c5-8307-4b0adf747899","year":2023},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.687062Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:6be744d93aaa84274b00082c7d1095105610e363ffea467315932bbe34c34642","observation_id":"58cf833e-c323-417d-b11f-b80cf442353d","resolution":{"observed_at":"2026-08-15T15:20:03.674993Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.654951Z","title":"Learning subpocket prototypes for generalizable structure-based drug design,","venue":null,"work_id":"2df59327-05e4-4ce8-b9d9-a990cf1e27d3","year":2023},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.692207Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:5df316f7a3877ce2e47a884bf25a48aa25bacfd322dd956ffe0baab73cf367e1","observation_id":"a1284859-3fb9-44d1-a3d6-6b2332040138","resolution":{"observed_at":"2026-08-15T15:20:03.660083Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.639378Z","title":"Flexsbdd: Structure-based drug design with flexible protein modeling,","venue":null,"work_id":"5d0bebea-ed3e-4ea1-8cf7-6ee8cd6f1839","year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.697312Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:f6e06f52ea713a2a999a4967e3406da6c65ddc3bc4d37a8c12831ed000591499","observation_id":"b8649bda-2e4f-4172-bf32-5ba207ecef45","resolution":{"observed_at":"2026-08-15T15:20:03.644289Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.623931Z","title":"Empower structure-based molecule optimization with gradient guided bayesian flow networks,","venue":null,"work_id":"b6619703-3d44-464e-bb2b-c5f25a22e3e0","year":2025},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.702077Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:a7f9471a68507556b42b946461621a513144512b57735302e12227a87196126f","observation_id":"6eb103ee-ce42-4578-9887-e8a17fd7972c","resolution":{"observed_at":"2026-08-15T15:20:03.628861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.608831Z","title":"Structure-aware dual-target drug design through collaborative learning of pharmacophore combination and molecular simulation,","venue":null,"work_id":"4d6f04b7-03f4-4b75-a482-45df8f1b4b8e","year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.706933Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:19f3996b1689633b3f5c84a75ee532880a693e9a1162007279c2df1cc315e2db","observation_id":"2fd909bd-145d-4b19-b43d-c9e44a04a946","resolution":{"observed_at":"2026-08-15T15:20:03.613847Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.592992Z","title":"Unified generative modeling of 3d molecules with bayesian flow networks,","venue":null,"work_id":"f06b9e06-554c-417b-871e-d38f9254c72d","year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.712147Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:b29326b6a0f9246f8a111155714ad3a4b05741802a11b0d940b8397263c485ff","observation_id":"c85c0494-4465-4c45-a838-582dc7282e69","resolution":{"observed_at":"2026-08-15T15:20:03.598444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.577749Z","title":"Image-to-image bayesian flow networks with structurally informative priors,","venue":null,"work_id":"b25f3fe3-140b-4bc8-a07f-1cfced5fb0de","year":2025},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.717239Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:d88e875facb341bb254efcfb582184f819d809dadad2b633e17c851db6a1cbce","observation_id":"7ddc6535-6d33-4fbb-b51c-42a3cb36851f","resolution":{"observed_at":"2026-08-15T15:20:03.582661Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.562965Z","title":"Target-guided bayesian flow networks for quantitatively constrained cad generation,","venue":null,"work_id":"9dee9c36-57e8-476f-b9c3-c361e9fbcb41","year":2025},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.722151Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:f61febcf4cfbc4f9f26c9162e38fc5fdc57e429f36d2ab6a847fd421f0a3bbf8","observation_id":"72aefe12-77eb-4a19-8d91-737fbdbb3a90","resolution":{"observed_at":"2026-08-15T15:20:03.567763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.546965Z","title":"Knowledge guided bayesian flow network for cad sequence generation","venue":null,"work_id":"f4e49b93-18e3-457b-a2f2-70a3b2b18986","year":null},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.726816Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:28c14b6b884c0d74eeff4d32eed974b0d5653b0c2e7aa799feb3bcaff9d268d9","observation_id":"e097dafc-2f45-47df-866d-623a5bdc4a5c","resolution":{"observed_at":"2026-08-15T15:20:03.551976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.531964Z","title":"Controllable molecule generation by sampling in continuous parameter space","venue":null,"work_id":"f6db8f0e-9107-44a3-959b-0fecbf4b0546","year":null},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.731856Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:0e50d1ac6a170227b0d7dd74c884533d2e5b2dc175eb76889c4d182889dd040f","observation_id":"4aa820f1-11cc-40ea-a130-c30cdc1c7177","resolution":{"observed_at":"2026-08-15T15:20:03.536701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.514283Z","title":"Protein sequence modelling with bayesian flow networks,","venue":null,"work_id":"80c7e0bd-aa9e-421f-8643-84bebf33ad59","year":2025},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.736425Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:fcbc011c2879e20d28f8f3af912e7b247c26123c1a1eddd10c98b996046e24d9","observation_id":"1e8aa3c1-1150-44b7-a3c3-9d0fc98abdc2","resolution":{"observed_at":"2026-08-15T15:20:03.520483Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.13280","last_updated":"2025-06-05T12:35:30Z","snapshot_observed_at":"2026-08-15T04:05:58.338658Z","submitted_at":"2024-11-20T12:48:29Z","title":"Empower Structure-Based Molecule Optimization with Gradient Guided Bayesian Flow Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.13280","snapshot_observed_at":"2026-08-15T15:20:02.741463Z","title":"Empower structure-based molecule optimization with gradient guided bayesian flow networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.741463Z"},"links":{"cited_paper":"/paper/2411.13280","citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:b6559c3f402dcc57282a70f8d1ecf62cbf6f947d9e6f7945c02984182b2dd456","observation_id":"2fdedc7c-2b52-4690-812f-58ea97d1fc30","resolution":{"observed_at":"2026-08-15T15:20:02.741463Z","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":"2511.14516","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T15:20:03.156841Z","title":"Full-atom peptide design via riemannian-euclidean bayesian flow networks,","venue":null,"work_id":"111d98e1-9840-4c6e-b97e-4604d37344f7","year":2025},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.746531Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:0ab488473564671366d5c57b03afc2a997845d55c4eca580dcdcc604a9817527","observation_id":"d15aaf09-9ac0-472a-837f-716039e9a947","resolution":{"observed_at":"2026-08-15T15:20:03.164994Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.07240","last_updated":"2021-07-30T11:45:08Z","snapshot_observed_at":"2026-08-18T18:13:33.479687Z","submitted_at":"2021-01-18T18:47:43Z","title":"Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts","version":2},"cited_work":{"arxiv_id":"2101.07240","doi":null,"metadata_source":"pith","pith_arxiv_id":"2101.07240","snapshot_observed_at":"2026-08-15T15:20:02.994468Z","title":"Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts","venue":"cs.LG","work_id":"4f4a21cb-025f-47b0-a940-13f99a161040","year":2021},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.752091Z"},"links":{"cited_paper":"/paper/2101.07240","citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:285d66b1bfb2adf591d3724ad0d4a478212654fb11fb8464731c356f57a7a2a3","observation_id":"59930de0-c989-45b2-90c1-9c0d4686b559","resolution":{"observed_at":"2026-08-15T15:20:03.002492Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.496848Z","title":"Multimodal conditional image synthesis with product-of-experts gans,","venue":null,"work_id":"e3e1c4c0-d776-49c7-a429-cf65ecfb55a0","year":2022},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.756608Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:f24d5bc407a3a55d05ee07e4427fba393e86aad41178f6682c37d5f18559d5dd","observation_id":"d56cc36d-1086-42cf-b919-c1e15e0050ad","resolution":{"observed_at":"2026-08-15T15:20:03.502580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.480353Z","title":"Equivariant diffusion for molecule generation in 3d,","venue":null,"work_id":"f3b00ed9-1bae-4218-9ce4-55a061dfc6ec","year":2022},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.761047Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:76db700db554f002a218c59bf96c51ab7ae6762d0c6e0fce8c29490c1d9014b2","observation_id":"ec31342d-a445-4dcb-a73c-0c1c8389b8bf","resolution":{"observed_at":"2026-08-15T15:20:03.485267Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.464909Z","title":"Equivariant flows: exact likelihood generative learning for symmetric densities,","venue":null,"work_id":"b9452752-0f85-4915-844b-b86a0cb49ace","year":2020},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.765413Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:e6914c6324d9ebace77307bbabfc72fa64f252ea68433672a5927c79c276f8e4","observation_id":"1758d4d7-01a5-4f0a-a497-6a2afc0f7d07","resolution":{"observed_at":"2026-08-15T15:20:03.470012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.450261Z","title":"E (n) equivariant normalizing flows,","venue":null,"work_id":"88cb9860-7f7e-491d-b5f5-a65c805a7eee","year":2021},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.769905Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:86e484c2f612256e92701ea6966634feb516019d8b3462919ce8b3973baa6fb0","observation_id":"fba4336f-ebf6-4a0a-a3be-1bcbe68c4261","resolution":{"observed_at":"2026-08-15T15:20:03.454897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.02923","last_updated":"2022-03-06T09:47:01Z","snapshot_observed_at":"2026-08-18T18:13:34.062574Z","submitted_at":"2022-03-06T09:47:01Z","title":"GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.02923","snapshot_observed_at":"2026-08-15T15:20:02.774183Z","title":"Geodiff: A geometric diffusion model for molecular conformation generation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.774183Z"},"links":{"cited_paper":"/paper/2203.02923","citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:0d3a4d282c00951a27d6e842695da595bb03d3b3fe8b4e6c9f46261e963151e0","observation_id":"c89c6b3a-d36c-4a2b-85e2-80ef72bd7117","resolution":{"observed_at":"2026-08-15T15:20:02.774183Z","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":"2026-08-15T15:20:03.434891Z","title":"Identification of cavities on protein sur- face using multiple computational approaches for drug binding site prediction,","venue":null,"work_id":"fa218656-220b-45ed-87f6-7da77176aaed","year":2011},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.778699Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:c1a5402be2d8de11005f61e9f8255152ff3f737864ec622e0deba774a6febdcc","observation_id":"e370cdd2-af50-42fa-ba5d-e09c14832bcc","resolution":{"observed_at":"2026-08-15T15:20:03.440241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.419357Z","title":"P2rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure,","venue":null,"work_id":"04146cef-ef2f-4404-a4aa-20291a36669f","year":2018},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.783136Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:22f61f8dae97a23ec150077568e2da7e2646582b43eb0b6f0591f6b383ef56d8","observation_id":"d9bb9e5e-1900-4e87-abc4-a85e094f2550","resolution":{"observed_at":"2026-08-15T15:20:03.424400Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:02.906408Z","title":"Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,","venue":null,"work_id":null,"year":1981},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.906408Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:5ca7f70af12b592e26ebb198a1d2d4f3abf45291c6968c584e85c7c5b7bb7165","observation_id":"03df53f0-62fb-4fab-bfda-7ea1ed811163","resolution":{"observed_at":"2026-08-15T15:20:02.906408Z","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":"2026-08-15T15:20:02.911516Z","title":"Method for registration of 3-d shapes,","venue":null,"work_id":null,"year":1992},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.911516Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:fa548deb510132f9c1da8c300c4a295bbd5900672ba6fa3b3c5da2d11ff60bee","observation_id":"e7fddf78-d829-49d0-acf6-c94cccfe55eb","resolution":{"observed_at":"2026-08-15T15:20:02.911516Z","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":"2026-08-15T15:20:03.384377Z","title":"Posecheck: Generative models for 3d structure-based drug design produce unrealistic poses,","venue":null,"work_id":"4f589fd3-4379-4abf-a9ba-38dc30875206","year":2023},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.916347Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:a8fec51afadb8862ef7b9c94ab7c120799015a225b77dd33738fa6985b0539fc","observation_id":"0bb73f53-affc-4b88-bcc7-4bb95dc310ec","resolution":{"observed_at":"2026-08-15T15:20:03.389382Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.370042Z","title":"Autodock vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading,","venue":null,"work_id":"70049f80-5e5f-4c13-a326-a26a6aa9ee33","year":2010},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.920888Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:6176af9d6d1b087f6c1c033d192bd4a1640ce23cfc50656af9028ddea9549bef","observation_id":"8b278530-3e26-4b4a-a52a-32164eb7f09e","resolution":{"observed_at":"2026-08-15T15:20:03.374600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:02.925487Z","title":"Quantifying the chemical beauty of drugs,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.925487Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:5e287fc3a1c04d5608cb9fcbca1ec382d8a24c7516bfba591bc7682131719ba4","observation_id":"a954b047-690d-4f4f-84d4-afe5d17105e8","resolution":{"observed_at":"2026-08-15T15:20:02.925487Z","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":"2026-08-15T15:20:03.345424Z","title":"Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions,","venue":null,"work_id":"c4e41f86-a76c-42db-8683-76619db040f9","year":2009},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.931117Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:e7acdaa256edca27402d632ba786cfd0c7185a0c3ba12a9827825ecc3f7355c1","observation_id":"d2246ee4-af6b-4518-8bdb-90aa25e9fef3","resolution":{"observed_at":"2026-08-15T15:20:03.349850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-15T15:20:03.330316Z","title":"Avg.”, “T-Avg","venue":null,"work_id":"c01e128a-683d-4453-b033-3a1bcc2d11bc","year":null},"citing_paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-15T15:20:02.936388Z"},"links":{"citing_paper":"/paper/2608.01007"},"observation_digest":"sha256:f7ab1cef0c7cb5305bd0ebda4534aa9f1d1cd2d4248b6f2265718e69780246c7","observation_id":"3f98075f-9079-4a94-8e64-82c48eee2557","resolution":{"observed_at":"2026-08-15T15:20:03.335348Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2608.01007","last_updated":"2026-08-02T05:23:26Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T18:11:04.193169Z","submitted_at":"2026-08-02T05:23:26Z","title":"Fused Bayesian Flow Networks for Dual-Target Molecular Design"},"reference_resolution":{"displayed":58,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":2,"verified_fuzzy":45},"total_outbound_references":58},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2608.01007."}