Paper Citation Record · LEDGER

IntervenGen: Interventional Data Generation for Robust and Data-Efficient Robot Imitation Learning

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2405.01472.

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

pith.paper-citation-record.v1
2405.01472 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T21:32:57.413751Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:01:27.655506Z

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 c5495716-30b1-4330-8148-a60285226522 · inbound

RaC: Robot Learning for Long-Horizon Tasks by Scaling Recovery and Correction cites this paper.

RaC: Robot Learning for Long-Horizon Tasks by Scaling Recovery and Correction IntervenGen: Interventional Data Generation for Robust and Data-Efficient Robot Imitation Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T21:32:57.413751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46cc5972-8349-481c-8072-5f5e0c067bdb · inbound

Good in Bad (GiB): Sifting Through End-user Demonstrations for Learning a Better Policy cites this paper.

Good in Bad (GiB): Sifting Through End-user Demonstrations for Learning a Better Policy IntervenGen: Interventional Data Generation for Robust and Data-Efficient Robot Imitation Learning

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:06:04.352326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 19782a0b-27fa-422e-a8cc-87b5f7786a88 · inbound

Good in Bad (GiB): Sifting Through End-user Demonstrations for Learning a Better Policy cites this paper.

Good in Bad (GiB): Sifting Through End-user Demonstrations for Learning a Better Policy IntervenGen: Interventional Data Generation for Robust and Data-Efficient Robot Imitation Learning

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:01:27.664885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6550d092-66f2-4ec2-868e-50fb230f28d4 · inbound

Data Pyramid for Embodied Manipulation: A Survey cites this paper.

Data Pyramid for Embodied Manipulation: A Survey IntervenGen: Interventional Data Generation for Robust and Data-Efficient Robot Imitation Learning

Reference 149

Resolution: unresolved; no resolver link, observed 2026-07-31T06:18:55.572499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.