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Paper Citation Record · LEDGER

Non-Adversarial Imitation Learning and its Connections to Adversarial Methods

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2008.03525.

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

pith.paper-citation-record.v1
2008.03525 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:11:51.654385Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T06:22:23.181975Z

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 ada6786a-2242-41bb-ae21-074c6aed4d3b · inbound

On Learning Informative Trajectory Embeddings for Imitation, Classification and Regression cites this paper.

On Learning Informative Trajectory Embeddings for Imitation, Classification and Regression Non-Adversarial Imitation Learning and its Connections to Adversarial Methods

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-10T20:11:51.654385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:11:51.654385Z digest=sha256:cb19a1e1f9f4aa88466cfa5b781a57a69cbcb35d87112eb44f91927bd35a77d5

Observation 205dd793-60b9-4425-8f25-4bd24ed16200 · inbound

Learning What to Do and What Not To Do: Offline Imitation from Expert and Undesirable Demonstrations cites this paper.

Learning What to Do and What Not To Do: Offline Imitation from Expert and Undesirable Demonstrations Non-Adversarial Imitation Learning and its Connections to Adversarial Methods

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:20.621562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:45:20.621562Z digest=sha256:5b45e0bcfdfcb20e3c0be0ee61e5a970821b0dc88c8240a37b286510649a097e

Observation a8633476-35f4-4d61-b3a8-af7018c2fe62 · inbound

Trust Region Inverse Reinforcement Learning: Explicit Dual Ascent using Local Policy Updates cites this paper.

Trust Region Inverse Reinforcement Learning: Explicit Dual Ascent using Local Policy Updates Non-Adversarial Imitation Learning and its Connections to Adversarial Methods

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:22:23.183416Z

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=arxiv_source observed=2026-05-13T06:21:50.117513Z digest=sha256:b06a2bce9e533cab4b89e1a170c3bba5c5412f71f1feea89566373558e0c4187