Paper Citation Record · LEDGER

Incentivized Learning in Principal-Agent Bandit Games

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2403.03811.

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

pith.paper-citation-record.v1
2403.03811 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:06:35.857737Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:03:58.240654Z

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 d717a5c1-c573-4be8-85ab-8b6131661045 · 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 Incentivized Learning in Principal-Agent Bandit Games

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T14:53:58.415367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62bd797d-15ec-4e52-ab61-0ffe285344b3 · 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 Incentivized Learning in Principal-Agent Bandit Games

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:03:58.299182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8d153045-f445-4694-8fde-817cf5a28029 · inbound

Fair Contracts in Principal-Agent Games with Heterogeneous Types cites this paper.

Fair Contracts in Principal-Agent Games with Heterogeneous Types Incentivized Learning in Principal-Agent Bandit Games

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T19:37:03.142696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 934ae663-e1f5-4ecc-84c5-659aa7ffef27 · inbound

Decentralized Multi-Player Q-Learning in Episodic Markov Decision Processes with Information Asymmetry cites this paper.

Decentralized Multi-Player Q-Learning in Episodic Markov Decision Processes with Information Asymmetry Incentivized Learning in Principal-Agent Bandit Games

Reference 140

Resolution: unresolved; no resolver link, observed 2026-08-16T00:06:35.857737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.