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Paper Citation Record · LEDGER

Text2Action: Generative Adversarial Synthesis from Language to Action

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1710.05298.

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

pith.paper-citation-record.v1
1710.05298 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 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:24:37.916246Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T18:16:16.850658Z

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 82f2c0d2-4c56-42c3-91ac-47b57a77f769 · 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 Text2Action: Generative Adversarial Synthesis from Language to Action

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T17:24:37.916246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:24:37.916246Z digest=sha256:0e9e20870456f010623388df4ffb1803b922f29ff8a2bfaa7f71f40d8925045b

Observation 9a527ddb-3112-44d7-b1d2-154ab9c71596 · inbound

Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward cites this paper.

Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward Text2Action: Generative Adversarial Synthesis from Language to Action

Reference 102

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:06:43.867483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T12:06:30.717999Z digest=sha256:d55dce756babb631b23320c961812dcdfc617bc6a823f44d2f1099f844538c62