Paper Citation Record · LEDGER

SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1905.11108.

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

pith.paper-citation-record.v1
1905.11108 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:21:45.511573Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T19:38:10.629575Z

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 ef801702-b70b-4f23-ae97-33d8d69a7a54 · inbound

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning cites this paper.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T12:21:45.511573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation adfc0d2e-f24c-41f9-a220-8b6384514e8b · 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 SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:22.644916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e506be4e-480a-4ccb-b3c5-bd0cce537a60 · inbound

Adaptive Accompaniment with ReaLchords cites this paper.

Adaptive Accompaniment with ReaLchords SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards

Reference 2010

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:09.752087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10074819-6656-4277-8120-92136c49b0d5 · inbound

Bootstrapping Reinforcement Learning with Sub-optimal Policies for Autonomous Driving cites this paper.

Bootstrapping Reinforcement Learning with Sub-optimal Policies for Autonomous Driving SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-05T06:00:50.687992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37aa0d7c-2066-41e3-a285-f57d78dcf75b · inbound

Efficient Vision-Language-Action Models for Embodied Manipulation: A Systematic Survey cites this paper.

Efficient Vision-Language-Action Models for Embodied Manipulation: A Systematic Survey SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-04T09:08:17.474960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94fe226b-e897-4673-bac3-b82485dd840a · inbound

Neural Operators for Multi-Task Control and Adaptation cites this paper.

Neural Operators for Multi-Task Control and Adaptation SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-13T19:38:10.631000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.