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Paper Citation Record · LEDGER

Human Motion Modeling using DVGANs

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1804.10652.

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

pith.paper-citation-record.v1
1804.10652 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:38:56.119339Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-06-28T23:02:46.053124Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • 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 097089fd-c9bc-418c-931a-a7216a8aa9ba · inbound

Learning Variations in Human Motion via Mix-and-Match Perturbation cites this paper.

Learning Variations in Human Motion via Mix-and-Match Perturbation Human Motion Modeling using DVGANs

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-14T15:38:56.119339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:38:56.119339Z digest=sha256:9576cc42421602a7f0e146ff0cf8f436da96a0c27804c0a1cec0aa0851454c71

Observation e189606e-74fa-48d5-924b-b6dc19de11a6 · inbound

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model cites this paper.

ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model Human Motion Modeling using DVGANs

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-11T12:13:11.923714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:13:11.923714Z digest=sha256:be40b4dc0b2e535c5902baee1d96811fa10a1989165a6bf563e6750d5829a27e

Observation f2efc9a3-3062-4955-a256-ed4951ca4aa1 · inbound

Strong and Controllable 3D Motion Generation cites this paper.

Strong and Controllable 3D Motion Generation Human Motion Modeling using DVGANs

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-09T22:44:28.946713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T22:44:28.946713Z digest=sha256:887c5eedfe3e33fef3acc3666bc065597afcd6e7d8ffc05defeaa52dfbd35ded

Observation 397af19d-02b7-4b82-9616-40503f931ec4 · inbound

Stochastic Human Motion Prediction with Memory of Action Transition and Action Characteristic cites this paper.

Stochastic Human Motion Prediction with Memory of Action Transition and Action Characteristic Human Motion Modeling using DVGANs

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T20:01:04.967576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:01:04.967576Z digest=sha256:03b03fb61edc95aea287b68485a983d592d78406a21c9225b302345c50f94677

Observation c7b8793d-d95d-4309-bcba-aaa02bd99b70 · inbound

Go to Zero: Towards Zero-shot Motion Generation with Million-scale Data cites this paper.

Go to Zero: Towards Zero-shot Motion Generation with Million-scale Data Human Motion Modeling using DVGANs

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T18:53:31.652875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:53:31.652875Z digest=sha256:ca66344255291156053b599d5e90a077617663763b52ac51274b3928054868f1

Observation ab8c5bd9-5b31-49b4-a5fd-5d37ae870ad4 · inbound

Omni-Supervised Motion Editing: Balancing Change and Invariance through Positive-Negative Learning cites this paper.

Omni-Supervised Motion Editing: Balancing Change and Invariance through Positive-Negative Learning Human Motion Modeling using DVGANs

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-06-28T23:02:46.054998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-28T23:01:37.408043Z digest=sha256:11e421c3c604dec0219d4e0a1bd909fa34ea61cfd0e3f32c4ddefe5eb9a2eb27