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Paper Citation Record · LEDGER

Unsupervised Image Representation Learning with Deep Latent Particles

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2205.15821.

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

pith.paper-citation-record.v1
2205.15821 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:01:03.996208Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T23:37:27.401428Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 073d133b-3f5b-441a-86df-9782cdc8e52d · inbound

Category-Agnostic Neural Object Rigging cites this paper.

Category-Agnostic Neural Object Rigging Unsupervised Image Representation Learning with Deep Latent Particles

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T14:01:03.996208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:01:03.996208Z digest=sha256:2bab9948660fb00c97f28a4d8a9330b90d94a0d774467bdc73f3189b68412e66

Observation 199e5a29-0852-44df-8212-7dd175174731 · inbound

Unifying Object-Centric World Models and Diffusion Policy: A Hierarchical Framework for Multi-Stage Robotic Tasks cites this paper.

Unifying Object-Centric World Models and Diffusion Policy: A Hierarchical Framework for Multi-Stage Robotic Tasks Unsupervised Image Representation Learning with Deep Latent Particles

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-02T23:37:27.403104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T18:08:00.023503Z digest=sha256:58ce84200c764982c728525a05b81d6ac4288c9e952c4a4a3c0b117378f9aaa2