{"as_of":"2026-08-15T13:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4088362c20e66f39b119eb31745d72e6852be35574902a38d94fa8d58caa05fd","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T21:51:33.590929Z","state":"measured"},{"denominator":25,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":25,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+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/2502.04730/citation-record","integrity":"/paper/2502.04730/integrity","json":"/paper/2502.04730/citation-record.json","paper":"/paper/2502.04730"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T21:51:34.155994Z","title":null,"venue":null,"work_id":"016e2c62-e31c-4b6d-8a09-d5b38c76bf44","year":2025},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.557305Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:4f3fae9f8e34f9a405a4668ea137545de69a27905df857c3926276a81cfb5704","observation_id":"4e2a6337-1016-42ff-8751-a27601c67d3d","resolution":{"observed_at":"2026-08-08T21:51:34.160586Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-08T21:51:33.481695Z","title":null,"venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.481695Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:7db09d3b9ecbfe2c865167e083b3abb88e33b08944543af4698548d977a144d5","observation_id":"a30fc68b-19fa-484b-8ddb-db01cdef8a70","resolution":{"observed_at":"2026-08-08T21:51:33.481695Z","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":"2026-08-08T21:51:34.169765Z","title":"Let τn = (Vn, En) be a tree topology with n (n ≤ N ) leaf nodes in X","venue":null,"work_id":"7fb3bd53-22e6-4be8-87bf-b188781f2d1e","year":2023},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.552545Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:62ef0a267a9a6b5ca1a94736cedc576af9ace0d9ced74b1f33914c1d58fc01f2","observation_id":"fb208299-dd93-450e-aa96-f5a17a89be15","resolution":{"observed_at":"2026-08-08T21:51:34.174310Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-08T21:51:34.126433Z","title":"16 Published as a conference paper at ICLR 2025 ABF HGE DC0.714286 (a) The pre-selected tree topology for the first peak","venue":null,"work_id":"dd69e068-dc09-4a29-9629-7c9dd8bb3073","year":1981},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.566675Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:282647cc2b31339d2a378ac2b146b904fe0010b7b0347ff87bd75600aaf692a4","observation_id":"506475ea-5bfc-4bae-b7f4-2f4d97d12db8","resolution":{"observed_at":"2026-08-08T21:51:34.131963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-08T21:51:34.111413Z","title":null,"venue":null,"work_id":"68806455-d7cd-47a1-9a15-6e9747c3e428","year":2005},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.571690Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:cf9f52e3ca0c28bd33a67dd26f98dded769c0047ebd02815c7d3b85c34c9dc9c","observation_id":"84a62c29-fa33-4781-b1b4-bb785bb740d1","resolution":{"observed_at":"2026-08-08T21:51:34.116167Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08774","last_updated":"2024-03-25T00:18:35Z","snapshot_observed_at":"2026-08-15T00:36:47.239045Z","submitted_at":"2023-10-12T23:46:08Z","title":"PhyloGFN: Phylogenetic inference with generative flow networks","version":2},"cited_work":{"arxiv_id":"2310.08774","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.08774","snapshot_observed_at":"2026-08-08T21:51:33.706650Z","title":"PhyloGFN: Phylogenetic inference with generative flow networks","venue":"q-bio.PE","work_id":"f2547315-778f-4b43-9e0e-7daa5ee62bed","year":2023},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.537423Z"},"links":{"cited_paper":"/paper/2310.08774","citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:0557d57002e89d9371abf7df6e00a5c11e637030a5b13936c367625de93223e5","observation_id":"f56e0f83-c535-491d-8f3e-d3923edc89f5","resolution":{"observed_at":"2026-08-08T21:51:33.712494Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-08T21:51:34.198424Z","title":"tree topology","venue":null,"work_id":"854d5937-7616-4b1e-8117-84d4b5cdce5c","year":2025},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.542526Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:da6de821b8ae0d3fa0967d5bcb1bcb0eec5bf4170144f3db73c5047f28e6a7ff","observation_id":"e8f36b0d-9f24-4e1d-86f2-1839923378c2","resolution":{"observed_at":"2026-08-08T21:51:34.202847Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-08T21:51:34.183797Z","title":"The sequential generating process in ARTree facilitates a probabilistic model over tree topologies which archives leading results in phylogenetic inference","venue":null,"work_id":"77690084-939a-4a9c-a67b-33ddf6918033","year":2023},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.547614Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:01c441046bc149e6feaa0c55340180989b789f4c44455af32529ff664ddf7607","observation_id":"59701bd6-6dcb-49e3-ba5a-72847c9b6f9d","resolution":{"observed_at":"2026-08-08T21:51:34.188614Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-08T21:51:34.141974Z","title":"D E XPERIMENTAL DETAILS For all experiments, PhyloV AE is implemented in PyTorch (Paszke et al., 2019)","venue":null,"work_id":"551d1260-a5e8-474c-9650-51c2282c1e4c","year":2019},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.561945Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:39f2627cd1ff43a4b3cb15523085e88205a10d3292da9ccda17bee105c6d58bc","observation_id":"c5aa12bd-01e6-4639-896b-a2708a21764f","resolution":{"observed_at":"2026-08-08T21:51:34.146672Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-08T21:51:34.065942Z","title":"20 Published as a conference paper at ICLR 2025 −4 −2 0 2 4 µ1 −4 −2 0 2 4 µ2 Mammal gene trees (seqlen =","venue":null,"work_id":"c19bbd9e-eec0-4561-b752-7fe402a2e93c","year":2025},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.586064Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:6bc36fa44209264060bcba550a7e7120ab6869ba1eff662056d7f74b635f283f","observation_id":"0e6fe253-753c-4d27-ad25-b4af19abe932","resolution":{"observed_at":"2026-08-08T21:51:34.071840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-08T21:51:34.053205Z","title":"ground truth on DS1","venue":null,"work_id":"1db4314a-7082-43bd-8266-7a3764c48c83","year":2025},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.590929Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:c2641c694c4f1bbd4519681f46d3071d6dea54a29cc836de64388068b4f23b0e","observation_id":"348f3283-6612-406d-93f6-3584a48b3ba1","resolution":{"observed_at":"2026-08-08T21:51:34.057110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-08T21:51:34.096786Z","title":"The experiments are run on a single 2.3 GHz CPU","venue":null,"work_id":"6db4d228-597d-4b4c-bf93-c568a74b122c","year":2018},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.576552Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:ba71e420a8de4561858fcbdc40a2c52fab074f4c450cc1bbb5c90dbac1a06593","observation_id":"fbd108df-be9b-42bd-8f0b-6aeb913d51e6","resolution":{"observed_at":"2026-08-08T21:51:34.101511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.05493","last_updated":"2017-09-22T21:36:00Z","snapshot_observed_at":"2026-08-14T22:22:33.292110Z","submitted_at":"2015-11-17T18:10:12Z","title":"Gated Graph Sequence Neural Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.05493","snapshot_observed_at":"2026-08-08T21:51:33.506135Z","title":"Gated graph sequence neural networks","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":1999,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.506135Z"},"links":{"cited_paper":"/paper/1511.05493","citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:d1a6a79a5eaab8d063b3be8a9516b564dfe2d57b795022a67b33717e417183c3","observation_id":"717937e2-cd29-4a11-b1b8-0483a552baf8","resolution":{"observed_at":"2026-08-08T21:51:33.506135Z","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":"10.1126/science.1067179","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"Science","work_id":"7c168fd4-2ed2-4bcb-9468-dd8f89b73535","year":null},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2001,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.514490Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:2fe505d1a7cd24109c2531fba5ce4be92196e5ecac23f2e08d557ec734630cf5","observation_id":"5f102ddb-58c5-47d2-8974-87970703be72","resolution":{"observed_at":"2026-08-08T21:51:33.668581Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-08T21:51:34.212291Z","title":null,"venue":null,"work_id":"91bf2196-8109-4167-b4ab-fccb6160d02a","year":2002},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2002,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.476227Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:35d8dd36c207f83e30e2c408d8dc81220394ee5232e623f55d076658ff0bbf91","observation_id":"f30f4485-0a28-4a3b-b11b-3382c1133159","resolution":{"observed_at":"2026-08-08T21:51:34.216852Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-08T21:51:34.081889Z","title":"These 6000 tree topologies with uniform weights constitute the training set of PhyloV AE","venue":null,"work_id":"f2b20b00-71d7-469c-a62d-c15a5dd4417e","year":2025},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2012,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.581281Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:407f2818e46d64ec0201f08271d25b98589a3005e11d16f7e8555bc32a18845a","observation_id":"9ce7521c-528c-4462-891e-c4408f2c8344","resolution":{"observed_at":"2026-08-08T21:51:34.086697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1093/sysbio/syt014","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"doi: 10.1093/ sysbio/syt014","venue":"Systematic Biology","work_id":"16a15125-4fe2-4cf4-883c-9110e8c1a82a","year":null},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.502075Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:023b2aaf0aaa995d277cd2eda198776f0773d57fca66a174133859f27d74c01f","observation_id":"4a73976c-b90b-4ce2-abb2-fedc49d53950","resolution":{"observed_at":"2026-08-08T21:51:33.682525Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1611.07308","last_updated":"2016-11-21T11:37:17Z","snapshot_observed_at":"2026-08-14T21:29:27.927932Z","submitted_at":"2016-11-21T11:37:17Z","title":"Variational Graph Auto-Encoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1611.07308","snapshot_observed_at":"2026-08-08T21:51:33.497073Z","title":"Variational graph auto-encoders.arXiv preprint arXiv:1611.07308,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.497073Z"},"links":{"cited_paper":"/paper/1611.07308","citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:9a0294ba88f98e478478422f2ded69ce26216f8a5a3d471d6f4df297ab0cdaa9","observation_id":"ca545a82-c711-4c4b-bb41-4b9930c25512","resolution":{"observed_at":"2026-08-08T21:51:33.497073Z","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":"2026-08-08T21:51:33.526806Z","title":"doi: 10.1093/sysbio/syv006","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.526806Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:ff2dd38796e8c7a8035389b08a0d34780dbac577a14c2becb55e6bd5a956e5d9","observation_id":"0ba16616-f93e-4dd8-879d-3c4d93503823","resolution":{"observed_at":"2026-08-08T21:51:33.526806Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1406.1078","last_updated":"2014-09-03T00:25:02Z","snapshot_observed_at":"2026-08-15T13:36:27.756066Z","submitted_at":"2014-06-03T17:47:08Z","title":"Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1406.1078","snapshot_observed_at":"2026-08-08T21:51:33.486724Z","title":"Learning phrase representations using RNN encoder-decoder for statistical machine translation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.486724Z"},"links":{"cited_paper":"/paper/1406.1078","citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:c3b85f907e6be79d8f496be895f89ced0b1b7c4b3f2e619d105184a9d0ab6fca","observation_id":"1ed9c05b-9df1-4e5c-91f2-233bbf1df312","resolution":{"observed_at":"2026-08-08T21:51:33.486724Z","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":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T21:51:34.023833Z","title":"doi: 10.1111/1755-0998.12676","venue":null,"work_id":"76100d76-0861-4cdb-a22e-18d843be4df2","year":null},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.492061Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:fc82200d266b1486923bf3e2c53c2883cd487b8d56f9271f3e498bcc03582b36","observation_id":"53200a25-e048-420b-a28a-443349ccba81","resolution":{"observed_at":"2026-08-08T21:51:34.028013Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1093/ve/vey016","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"doi: 10.1093/ve/vey016","venue":"Virus Evolution","work_id":"1fe84f35-19c5-466f-ba4b-6cf6c0b77441","year":2025},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.522510Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:431548b2fdfc0d2664f5b43d9cb4e78557e84cb85b740318b29851a8cd3abd50","observation_id":"c9741f9d-92b1-4c8c-8283-99ebe3dbbbfd","resolution":{"observed_at":"2026-08-08T21:51:33.638750Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1909.02480","last_updated":"2019-10-09T05:37:40Z","snapshot_observed_at":"2026-08-15T12:50:42.398865Z","submitted_at":"2019-09-05T15:32:34Z","title":"FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.02480","snapshot_observed_at":"2026-08-08T21:51:33.510290Z","title":"Flowseq: Non-autoregressive conditional sequence generation with generative flow","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.510290Z"},"links":{"cited_paper":"/paper/1909.02480","citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:3bb23b600dcd5b2f8c0ae16f2c468a38cc83eab79deae16ebbca7d2a062df050","observation_id":"8672715f-a198-4a25-9541-8ae0143a1c61","resolution":{"observed_at":"2026-08-08T21:51:33.510290Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.05058","last_updated":"2024-08-09T13:29:08Z","snapshot_observed_at":"2026-08-15T06:04:17.983828Z","submitted_at":"2024-08-09T13:29:08Z","title":"Variational Bayesian Phylogenetic Inference with Semi-implicit Branch Length Distributions","version":1},"cited_work":{"arxiv_id":"2408.05058","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.05058","snapshot_observed_at":"2026-08-08T21:51:33.727814Z","title":"Variational Bayesian Phylogenetic Inference with Semi-implicit Branch Length Distributions","venue":"stat.ML","work_id":"c6d91423-bd9f-4a2c-a6f9-7031dd86aa09","year":2024},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.532323Z"},"links":{"cited_paper":"/paper/2408.05058","citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:c84d9f6537fd7b437a534bac20656072769f5417b8b32ed523db652f77cc41c2","observation_id":"901de3f4-b0e3-491c-b751-6028b39a5144","resolution":{"observed_at":"2026-08-08T21:51:33.732648Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1093/sysbio/syae030","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"doi: 10.1093/sysbio/syae030","venue":"Systematic Biology","work_id":"6095f297-2d2e-4a47-ac33-68e6e91251ed","year":null},"citing_paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-08T21:51:33.518631Z"},"links":{"citing_paper":"/paper/2502.04730"},"observation_digest":"sha256:03177bafb5aa241bf085c844767fd4952b4b285dc6319df92d3ae3cef2831c85","observation_id":"ae852c7a-54a0-444b-82ed-3ee041a7d3ce","resolution":{"observed_at":"2026-08-08T21:51:33.654069Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.04730","last_updated":"2025-02-07T07:58:47Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-15T01:53:27.506293Z","submitted_at":"2025-02-07T07:58:47Z","title":"PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":9,"verified_exact":6,"verified_fuzzy":9},"total_outbound_references":25},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2502.04730."}