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Paper Citation Record · LEDGER

Contractual Reinforcement Learning: Pulling Arms with Invisible Hands

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.01458.

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

pith.paper-citation-record.v1
2407.01458 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:53:10.808207Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T09:18:31.674359Z

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 e4590607-40c1-406b-8804-84ec0ad94f9b · inbound

Principal-Agent Bandit Games with Self-Interested and Exploratory Learning Agents cites this paper.

Principal-Agent Bandit Games with Self-Interested and Exploratory Learning Agents Contractual Reinforcement Learning: Pulling Arms with Invisible Hands

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-11T10:53:10.808207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:53:10.808207Z digest=sha256:ffa427b45386e3882e8808069aaf81faa5d3544d611796adccd7332c34c81d8c

Observation 3633a0f4-bd5d-4451-9828-c2005aa4d3f7 · inbound

Algorithmic Contract Theory: A Survey cites this paper.

Algorithmic Contract Theory: A Survey Contractual Reinforcement Learning: Pulling Arms with Invisible Hands

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-11T10:43:26.736947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:43:26.736947Z digest=sha256:e708a9ebd75b10eff1a9ad68fc9418ca081856ad05ee098986422a5b0da6b278

Observation 475dff40-5cf1-4c99-9a6c-962f66fa311a · inbound

Provably Efficient Algorithm for Best Scoring Rule Identification in Online Principal-Agent Information Acquisition cites this paper.

Provably Efficient Algorithm for Best Scoring Rule Identification in Online Principal-Agent Information Acquisition Contractual Reinforcement Learning: Pulling Arms with Invisible Hands

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T14:53:58.959421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:53:58.959421Z digest=sha256:61799ccfaee34cf43605e207f7cc460453859bdef57b49d68b8aba42e17c69db

Observation 46d66d4f-ee05-4395-9569-8465266007b3 · inbound

Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals cites this paper.

Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals Contractual Reinforcement Learning: Pulling Arms with Invisible Hands

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T13:03:57.940291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:03:57.940291Z digest=sha256:86a2cd7f803b1b9cf1126b22c8e9605e4277e290de9d759438c8b6ededd79e04

Observation 1ac80fa5-4b33-43c1-8cc2-a7d960748499 · inbound

The Power of Information for Intermediate States in Contract Design cites this paper.

The Power of Information for Intermediate States in Contract Design Contractual Reinforcement Learning: Pulling Arms with Invisible Hands

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:18:31.676587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T08:03:47.774614Z digest=sha256:9e861fad072ed2876c6d344914f619bc737388bccf60df67d95302d20a2e1ff2