Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2110.04184.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T05:00:57.614294Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-24T09:34:16.945669Z
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 e8c3dcc4-92e0-40fa-9a79-be50fab55608 · inbound
Learning Strategic Value and Cooperation in Multi-Player Stochastic Games through Side Payments cites this paper.
Learning Strategic Value and Cooperation in Multi-Player Stochastic Games through Side Payments When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T09:34:16.948297Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4df6750a-8ad8-4153-98ff-fc5ce1da62c0 · inbound
Provable Partially Observable Reinforcement Learning with Privileged Information cites this paper.
Provable Partially Observable Reinforcement Learning with Privileged Information When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:00:57.614294Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d2895eaa-edec-4d2a-8aaa-4105d8e89c17 · inbound
Minimax-Optimal Multi-Agent Robust Reinforcement Learning cites this paper.
Minimax-Optimal Multi-Agent Robust Reinforcement Learning When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T00:10:22.369597Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7192e4ea-b008-49b5-b477-c802699f76bf · inbound
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games cites this paper.
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T20:38:32.895105Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9fed3e9f-c937-4f07-b473-bc9380fc8aac · inbound
Solving Zero-Sum Convex Markov Games cites this paper.
Solving Zero-Sum Convex Markov Games When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Reference 109
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:55:55.667677Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d00149d9-cf56-4d0d-94d6-dd1622a928da · inbound
Corruption-robust Offline Multi-agent Reinforcement Learning From Human Feedback cites this paper.
Corruption-robust Offline Multi-agent Reinforcement Learning From Human Feedback When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T21:19:29.020075Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9db4e1d0-8d1c-448f-abbc-2afdf638af36 · inbound
Finite-Time Analysis of Q-Value Iteration for General-Sum Stackelberg Games cites this paper.
Finite-Time Analysis of Q-Value Iteration for General-Sum Stackelberg Games When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T22:30:50.058377Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 02aa6b85-a6f5-4dd6-9a0a-cf8a1a2f725d · inbound
Taming the Curses of Multiagency in Robust Markov Games with Large State Space through Linear Function Approximation cites this paper.
Taming the Curses of Multiagency in Robust Markov Games with Large State Space through Linear Function Approximation When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T06:00:35.889817Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1d065284-5fc6-4f8e-b578-a41cf3fee67c · inbound
Sample-efficient inductive matrix completion with noise and inexact side-information cites this paper.
Sample-efficient inductive matrix completion with noise and inexact side-information When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
Reference 157
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-20T14:08:21.102090Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.