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Paper Citation Record · LEDGER

Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.10796.

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

pith.paper-citation-record.v1
2302.10796 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 2026-08-06T20:53:53.706900Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:57:41.498928Z

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 ababe30b-1db1-4bb3-947b-19622a51b47c · inbound

Quantum reinforcement learning in dynamic environments cites this paper.

Quantum reinforcement learning in dynamic environments Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:53.706900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:53.706900Z digest=sha256:720e257f61ded97dbbf7f6326eac5f5ee113315946dd8ee6fd90186f821162e7

Observation d52ee81a-1db6-4ab8-a5ef-eff87edfff8f · inbound

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities cites this paper.

Quantum Algorithms for Bandits with Knapsacks with Improved Regret and Time Complexities Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret

Reference 64

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:57:41.560901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:57:40.501641Z digest=sha256:7f5ba3842de306575dcc35eb128233f1b1e6f6dad2661b063538b9b052053861