Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2301.06052.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:50:08.856786Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T18:13:48.481235Z
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 678e7055-e8b9-485b-8439-eadcb6b9647b · inbound
MSDformer: Multi-scale Discrete Transformer For Time Series Generation cites this paper.
MSDformer: Multi-scale Discrete Transformer For Time Series Generation T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
Reference 54
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T13:44:52.864469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 693afb26-81c7-471f-aa18-a8119ba42eae · inbound
Music-Aligned Holistic 3D Dance Generation via Hierarchical Motion Modeling cites this paper.
Music-Aligned Holistic 3D Dance Generation via Hierarchical Motion Modeling T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:50:08.856786Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3965b005-6eb6-4a0a-a7dd-b44e4c00a38c · inbound
ExpertEdit: Learning Skill-Aware Motion Editing from Expert Videos cites this paper.
ExpertEdit: Learning Skill-Aware Motion Editing from Expert Videos T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
Reference 67
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T11:01:13.196991Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9ec621af-d7da-44f6-a773-210c50e5192a · inbound
SDFlow: Similarity-Driven Flow Matching for Time Series Generation cites this paper.
SDFlow: Similarity-Driven Flow Matching for Time Series Generation T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
Reference 30
- Resolution
- malformed identifier
- arxiv_id, observed 2026-05-11T19:31:10.867246Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3c7a16f2-e5b7-4bab-94dd-a963aa8ba8dd · inbound
SDFlow: Similarity-Driven Flow Matching for Time Series Generation cites this paper.
SDFlow: Similarity-Driven Flow Matching for Time Series Generation T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
Reference 31
- Resolution
- malformed identifier
- arxiv_id, observed 2026-05-12T07:06:28.330590Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 887bfdc1-c570-4bf4-bf22-b6fc40255ffe · inbound
ScaleMoGen: Autoregressive Next-Scale Prediction for Human Motion Generation cites this paper.
ScaleMoGen: Autoregressive Next-Scale Prediction for Human Motion Generation T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
Reference 41
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T06:27:24.785978Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7af403c7-f6d6-4499-8655-0ba52bb6bb09 · inbound
ScaleMoGen: Autoregressive Next-Scale Prediction for Human Motion Generation cites this paper.
ScaleMoGen: Autoregressive Next-Scale Prediction for Human Motion Generation T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T14:19:03.954128Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e90b632d-3157-428d-9561-34246629d960 · inbound
Natural Human Motion Recovery by Aligning High-Order Temporal Dynamics from Monocular Videos cites this paper.
Natural Human Motion Recovery by Aligning High-Order Temporal Dynamics from Monocular Videos T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
Reference 48
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T18:13:48.483101Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8cf8a982-e813-486f-85a3-50534511f0e0 · inbound
AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked Modeling cites this paper.
AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked Modeling T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T08:53:15.595427Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0a8df728-d112-41da-89f5-79700947e755 · inbound
MoRAE: Flow-Friendly Self-Supervised Latents for Text-to-Motion Generation cites this paper.
MoRAE: Flow-Friendly Self-Supervised Latents for Text-to-Motion Generation T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T12:14:40.345769Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.