Paper Citation Record · LEDGER

CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2310.12972.

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

pith.paper-citation-record.v1
2310.12972 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:06:33.783050Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:19:37.599626Z

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 753119fa-dd5c-4897-9c39-019c57de71f3 · inbound

Latent Policy Barrier: Learning Robust Visuomotor Policies by Staying In-Distribution cites this paper.

Latent Policy Barrier: Learning Robust Visuomotor Policies by Staying In-Distribution CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T23:06:33.783050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f49f0e5a-5109-4ad5-8eaa-5295b9a00c6d · 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 CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T21:32:57.575867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a8f1ca8-9c55-422b-9214-e9a3ef1746d9 · inbound

Combined Constrained Sampling and Reinforcement Learning for Robotic Manipulation cites this paper.

Combined Constrained Sampling and Reinforcement Learning for Robotic Manipulation CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T03:18:42.641224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ad9138f-0b13-46bd-ad64-94259705c2d0 · inbound

From Prior to Pro: Efficient Skill Mastery via Distribution Contractive RL Finetuning cites this paper.

From Prior to Pro: Efficient Skill Mastery via Distribution Contractive RL Finetuning CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-14T23:46:32.301737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a865257-69c2-4a09-b066-d3f9d5866158 · inbound

QHyer: Q-conditioned Hybrid Attention-mamba Transformer for Offline Goal-conditioned RL cites this paper.

QHyer: Q-conditioned Hybrid Attention-mamba Transformer for Offline Goal-conditioned RL CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:30:58.607760Z

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.

Observation 9c24af7b-5357-45a3-b408-797bebf9b27b · inbound

One Demo is Worth a Thousand Trajectories: Action-View Augmentation for Visuomotor Policies cites this paper.

One Demo is Worth a Thousand Trajectories: Action-View Augmentation for Visuomotor Policies CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-04T01:19:20.788341Z

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.

Observation 36c31a28-167e-4421-ad29-1f6e365a1cd0 · inbound

Robot Self-Improvement via Human-Video Dynamics Models cites this paper.

Robot Self-Improvement via Human-Video Dynamics Models CCIL: Continuity-based Data Augmentation for Corrective Imitation Learning

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-07-04T06:19:37.600992Z

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.