Paper Citation Record · LEDGER

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders

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.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.04730 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:51:33.590929Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

verified exact6
verified fuzzy9
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4e2a6337-1016-42ff-8751-a27601c67d3d · outbound

This paper cites an unresolved cited work.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-08T21:51:34.160586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a30fc68b-19fa-484b-8ddb-db01cdef8a70 · outbound

This paper cites an unresolved cited work.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T21:51:33.481695Z

Source-reported events for the cited work

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Observation fb208299-dd93-450e-aa96-f5a17a89be15 · outbound

This paper cites Let τn = (Vn, En) be a tree topology with n (n ≤ N ) leaf nodes in X.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders Let τn = (Vn, En) be a tree topology with n (n ≤ N ) leaf nodes in X

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:51:34.174310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 506475ea-5bfc-4bae-b7f4-2f4d97d12db8 · outbound

This paper cites 16 Published as a conference paper at ICLR 2025 ABF HGE DC0.714286 (a) The pre-selected tree topology for the first peak.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders 16 Published as a conference paper at ICLR 2025 ABF HGE DC0.714286 (a) The pre-selected tree topology for the first peak

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:51:34.131963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 84a62c29-fa33-4781-b1b4-bb785bb740d1 · outbound

This paper cites an unresolved cited work.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-08T21:51:34.116167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f56e0f83-c535-491d-8f3e-d3923edc89f5 · outbound

This paper cites PhyloGFN: Phylogenetic inference with generative flow networks.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders PhyloGFN: Phylogenetic inference with generative flow networks

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T21:51:33.712494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e8f36b0d-9f24-4e1d-86f2-1839923378c2 · outbound

This paper cites tree topology.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders tree topology

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:51:34.202847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 59701bd6-6dcb-49e3-ba5a-72847c9b6f9d · outbound

This paper cites The sequential generating process in ARTree facilitates a probabilistic model over tree topologies which archives leading results in phylogenetic inference.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders The sequential generating process in ARTree facilitates a probabilistic model over tree topologies which archives leading results in phylogenetic inference

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:51:34.188614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c5aa12bd-01e6-4639-896b-a2708a21764f · outbound

This paper cites D E XPERIMENTAL DETAILS For all experiments, PhyloV AE is implemented in PyTorch (Paszke et al., 2019).

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders D E XPERIMENTAL DETAILS For all experiments, PhyloV AE is implemented in PyTorch (Paszke et al., 2019)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:51:34.146672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0e6fe253-753c-4d27-ad25-b4af19abe932 · outbound

This paper cites 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 =.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders 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 =

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:51:34.071840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 348f3283-6612-406d-93f6-3584a48b3ba1 · outbound

This paper cites ground truth on DS1.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders ground truth on DS1

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:51:34.057110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fbd108df-be9b-42bd-8f0b-6aeb913d51e6 · outbound

This paper cites The experiments are run on a single 2.3 GHz CPU.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders The experiments are run on a single 2.3 GHz CPU

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:51:34.101511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 717937e2-cd29-4a11-b1b8-0483a552baf8 · outbound

This paper cites Gated Graph Sequence Neural Networks.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders Gated Graph Sequence Neural Networks

Reference 1999

Resolution: unresolved; no resolver link, observed 2026-08-08T21:51:33.506135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f102ddb-58c5-47d2-8974-87970703be72 · outbound

This paper cites an unresolved cited work.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders Unresolved cited work

Reference 2001

Resolution: verified exact; doi, observed 2026-08-08T21:51:33.668581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f30f4485-0a28-4a3b-b11b-3382c1133159 · outbound

This paper cites an unresolved cited work.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders Unresolved cited work

Reference 2002

Resolution: unresolved; raw_fallback, observed 2026-08-08T21:51:34.216852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9ce7521c-528c-4462-891e-c4408f2c8344 · outbound

This paper cites These 6000 tree topologies with uniform weights constitute the training set of PhyloV AE.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders These 6000 tree topologies with uniform weights constitute the training set of PhyloV AE

Reference 2012

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T21:51:34.086697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4a73976c-b90b-4ce2-abb2-fedc49d53950 · outbound

This paper cites doi: 10.1093/ sysbio/syt014.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders doi: 10.1093/ sysbio/syt014

Reference 2013

Resolution: verified exact; doi, observed 2026-08-08T21:51:33.682525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ca545a82-c711-4c4b-bb41-4b9930c25512 · outbound

This paper cites Variational Graph Auto-Encoders.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders Variational Graph Auto-Encoders

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-08T21:51:33.497073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ba16616-f93e-4dd8-879d-3c4d93503823 · outbound

This paper cites doi: 10.1093/sysbio/syv006.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders doi: 10.1093/sysbio/syv006

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-08T21:51:33.526806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ed9c05b-9df1-4e5c-91f2-233bbf1df312 · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-08T21:51:33.486724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53200a25-e048-420b-a28a-443349ccba81 · outbound

This paper cites doi: 10.1111/1755-0998.12676.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders doi: 10.1111/1755-0998.12676

Reference 2017

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-08T21:51:34.028013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c9741f9d-92b1-4c8c-8283-99ebe3dbbbfd · outbound

This paper cites doi: 10.1093/ve/vey016.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders doi: 10.1093/ve/vey016

Reference 2018

Resolution: verified exact; doi, observed 2026-08-08T21:51:33.638750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8672715f-a198-4a25-9541-8ae0143a1c61 · outbound

This paper cites FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-08T21:51:33.510290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 901de3f4-b0e3-491c-b751-6028b39a5144 · outbound

This paper cites Variational Bayesian Phylogenetic Inference with Semi-implicit Branch Length Distributions.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders Variational Bayesian Phylogenetic Inference with Semi-implicit Branch Length Distributions

Reference 2023

Resolution: verified exact; local_arxiv, observed 2026-08-08T21:51:33.732648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ae852c7a-54a0-444b-82ed-3ee041a7d3ce · outbound

This paper cites doi: 10.1093/sysbio/syae030.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders doi: 10.1093/sysbio/syae030

Reference 2024

Resolution: verified exact; doi, observed 2026-08-08T21:51:33.654069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.