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Paper Citation Record · LEDGER

Disentangling factors of variation in deep representations using adversarial training

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1611.03383.

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

pith.paper-citation-record.v1
1611.03383 v1

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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T06:57:46.427161Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 f1d9d5ba-8cbf-491b-91be-62511c6a593e · inbound

XFACTORS: Disentangled Information Bottleneck via Contrastive Supervision cites this paper.

XFACTORS: Disentangled Information Bottleneck via Contrastive Supervision Disentangling factors of variation in deep representations using adversarial training

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-03T06:57:46.427161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:57:46.427161Z digest=sha256:b76f0d3ae829d0fa5110434fb857925889f9b780f4337e8ab9185ae0377ec726

Observation 67c74862-7d94-4424-b667-0e3cfc00d87f · inbound

Towards Dual-Brain Minimal Sufficient Representation for Vision-Language Navigation cites this paper.

Towards Dual-Brain Minimal Sufficient Representation for Vision-Language Navigation Disentangling factors of variation in deep representations using adversarial training

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-01T03:26:16.377030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T03:26:16.377030Z digest=sha256:70f6aa2eb650730c465fa3e9902018a28fc7393937685b7b383bc3a177b9de9c