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Paper Citation Record · LEDGER

Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.18076.

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

pith.paper-citation-record.v1
2410.18076 v4

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 2026-08-12T06:34:41.77262+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:21:18.434308Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T10:45:42.670765Z

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 5944f1a6-f8ea-44a9-90e7-e9a2249fdadb · inbound

Exploratory Diffusion Model for Unsupervised Reinforcement Learning cites this paper.

Exploratory Diffusion Model for Unsupervised Reinforcement Learning Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-08T13:21:18.434308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:21:18.434308Z digest=sha256:e18d2f75f79e15d84ca1033506ac22a7f018d5c43994d46f8033e715deed3715

Observation 976b5ffd-4f42-4c9f-8400-7b0363671a0f · inbound

Reinforcement Learning with Action Chunking cites this paper.

Reinforcement Learning with Action Chunking Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-05-19T05:22:06.465093Z

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=pdf_text observed=2026-05-19T05:18:20.960945Z digest=sha256:cadd8962e8dfda945e5d0bdd504a4bb9a6867712e1a70b7eee670282ed7e881c

Observation 33a8a429-6049-4687-997f-bd57fc282f9c · inbound

Behavioral Exploration: Learning to Explore via In-Context Adaptation cites this paper.

Behavioral Exploration: Learning to Explore via In-Context Adaptation Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T18:15:47.138620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:15:47.138620Z digest=sha256:ef53be1e64810938cd01ab7aee6000aa87c90f9b425e9f1df168cfbf0bd5978f

Observation a43c6606-8c5d-4127-8dbb-ec086f4aabcb · inbound

World Action Verifier: Self-Improving World Models via Forward-Inverse Asymmetry cites this paper.

World Action Verifier: Self-Improving World Models via Forward-Inverse Asymmetry Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration

Reference 121

Resolution
unresolved
no resolver link, observed 2026-07-13T14:05:26.303000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T14:05:26.303000Z digest=sha256:12775c9391816fffc413208d26e27df736d4d880ba9ddb175bcecf16e525cc4e

Observation 2722712f-3f00-42b3-93ae-daaa1aa40e63 · inbound

Adapting Generalist Robot Policies with Semantic Reinforcement Learning cites this paper.

Adapting Generalist Robot Policies with Semantic Reinforcement Learning Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-07-01T10:45:42.672024Z

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=pdf_text observed=2026-07-01T05:09:29.625066Z digest=sha256:dce2892a08418812896bf1c071672f6cf430e005b5fc6e3191aff8cb5fb747d4

Observation a8653a43-5ca3-403c-9606-da4b949fe954 · inbound

Expert Behavior Prior Reinforcement Learning cites this paper.

Expert Behavior Prior Reinforcement Learning Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-01T07:56:31.151219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T07:56:31.151219Z digest=sha256:6cc6646e29d453973fda7dea5cff922eeeac2359c9fd40735fb6ed3069eedbcc