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Paper Citation Record · LEDGER

Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2205.11140.

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

pith.paper-citation-record.v1
2205.11140 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 2026-08-07T12:43:47.660403Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:09:51.305130Z

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 bf60b172-58a5-4b1c-a562-17d5db2b54ab · inbound

Thompson Sampling in Online RLHF with General Function Approximation cites this paper.

Thompson Sampling in Online RLHF with General Function Approximation Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T12:43:47.660403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:43:47.660403Z digest=sha256:fdc720bbf5527e07ada586db85ce82d6340b00d8c5cb71e100a11e41e054e676

Observation 57e59c0f-f7ed-4906-ad64-af922c89c8ca · inbound

Finding Stationary Points by Comparisons cites this paper.

Finding Stationary Points by Comparisons Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:09:51.306394Z

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=2026-06-26T05:26:07.720218Z digest=sha256:13f84a60455891e45a88bcafb449bbff33f502cd09eb79762af98d767b3b5f36