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Paper Citation Record · LEDGER

Fast active learning for pure exploration in reinforcement learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2007.13442.

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

pith.paper-citation-record.v1
2007.13442 v2

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 2026-08-02T20:42:07.929118Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 81fd62dc-2065-4699-8421-6631877d0a90 · inbound

Multi-agent imitation learning with function approximation: Linear Markov games and beyond cites this paper.

Multi-agent imitation learning with function approximation: Linear Markov games and beyond Fast active learning for pure exploration in reinforcement learning

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-02T20:42:07.929118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:42:07.929118Z digest=sha256:73d8745234e936b3edaec17be36646f779b93dc79f101ed520cb6547940de642

Observation 035993e8-4204-4e8e-a8f1-0c3b7b4507ef · inbound

Information-Based Exploration via Random Features for Reinforcement Learning cites this paper.

Information-Based Exploration via Random Features for Reinforcement Learning Fast active learning for pure exploration in reinforcement learning

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-01T16:35:02.988914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T16:35:02.988914Z digest=sha256:2eea1e81d9959e62782d235ff672b0be71fd49d8ff1b5fdd875b4e4380398106