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Paper Citation Record · LEDGER

Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.14519.

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

pith.paper-citation-record.v1
2411.14519 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:07:25.504405Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T15:42:41.519963Z

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 e1d8b0a8-5381-4bc9-bd51-22bf5b3618a4 · inbound

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers cites this paper.

VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T21:07:25.504405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:07:25.504405Z digest=sha256:23b98263143ccfec5e4a821a7c2f6c5616c5febd83b790a4b708149d6461677f

Observation 48604d1a-4b26-428d-809a-6c534db4262f · inbound

DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge cites this paper.

DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-16T15:42:41.521798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-16T15:42:41.363422Z digest=sha256:ecbf5a6779e58d3598835f48fe88425504103091db3ce28da0a952112de6207e