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Paper Citation Record · LEDGER

Safety-Aware Imitation Learning via MPC-Guided Disturbance Injection

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2508.03129.

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

pith.paper-citation-record.v1
2508.03129 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:00:06.381907Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T20:32:37.533073Z

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 8fd0dd93-13da-4f7f-bbe4-889746d7fcda · inbound

Unsupervised Discovery of Failure Taxonomies from Deployment Logs cites this paper.

Unsupervised Discovery of Failure Taxonomies from Deployment Logs Safety-Aware Imitation Learning via MPC-Guided Disturbance Injection

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T06:00:06.381907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:00:06.381907Z digest=sha256:5158a578ca0c1f1459b4c49976c4c860fce3dfcb2b76ade2db606deccf93c528

Observation 2cbb3eb3-cfb3-41fd-9b22-3fddc56162e2 · inbound

Infeasible optimization problems and the hierarchical augmented Lagrangian method in imitation learning cites this paper.

Infeasible optimization problems and the hierarchical augmented Lagrangian method in imitation learning Safety-Aware Imitation Learning via MPC-Guided Disturbance Injection

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-28T20:32:37.535797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-28T18:37:04.298448Z digest=sha256:420fd52f567a623c88f81a6f7b028201cb1766c04b5aeb967d14180788d22b5e