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Paper Citation Record · LEDGER

PoseGPT: Quantization-based 3D Human Motion Generation and Forecasting

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2210.10542.

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

pith.paper-citation-record.v1
2210.10542 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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:24:38.218410Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:36:18.021504Z

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 99950b1c-ed64-4cd7-859b-67ba801539a0 · inbound

Motion Generation Review: Exploring Deep Learning for Lifelike Animation with Manifold cites this paper.

Motion Generation Review: Exploring Deep Learning for Lifelike Animation with Manifold PoseGPT: Quantization-based 3D Human Motion Generation and Forecasting

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T17:24:38.218410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:24:38.218410Z digest=sha256:e1ad1629151d27c8f92eae34f4761631cf478db505a0515fba6cbb1d44aa3963

Observation b40480cc-ea3f-4d1c-b85e-275ad99997a6 · inbound

Ultra Diffusion Poser: Diffusion-Based Human Motion Tracking From Sparse Inertial Sensors and Ranging-Based Between-Sensor Distances cites this paper.

Ultra Diffusion Poser: Diffusion-Based Human Motion Tracking From Sparse Inertial Sensors and Ranging-Based Between-Sensor Distances PoseGPT: Quantization-based 3D Human Motion Generation and Forecasting

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-07-01T22:36:18.022949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-28T15:08:49.377430Z digest=sha256:400c53c966db24e8f8c97f9036587b6a105c41350f9d6ad0fb3c705e49d0d379