Paper Citation Record · LEDGER

Convergence of Learning Dynamics in Stackelberg Games

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1906.01217.

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

pith.paper-citation-record.v1
1906.01217 v3

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 2026-08-18T06:34:40.430872+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:56:25.371500Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:46:55.270200Z

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 2782d914-a3d3-4fc8-9b2b-3e640db6e1b0 · inbound

Finding a Multiple Follower Stackelberg Equilibrium: A Fully First-Order Method cites this paper.

Finding a Multiple Follower Stackelberg Equilibrium: A Fully First-Order Method Convergence of Learning Dynamics in Stackelberg Games

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T21:22:14.071688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f50957c-8e16-4e25-8907-7ea24e96a685 · inbound

Learning in Stackelberg Markov Games cites this paper.

Learning in Stackelberg Markov Games Convergence of Learning Dynamics in Stackelberg Games

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T15:56:25.371500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a2e194d-9d0c-4b16-b7ae-a0be53d568ff · 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 Convergence of Learning Dynamics in Stackelberg Games

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:30:50.032330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 153b44cd-6043-4952-b0b8-57c61848ea7c · inbound

Near-Optimal Last-Iterate Convergence for Zero-Sum Games with Bandit Feedback and Opponent Actions cites this paper.

Near-Optimal Last-Iterate Convergence for Zero-Sum Games with Bandit Feedback and Opponent Actions Convergence of Learning Dynamics in Stackelberg Games

Reference 115

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:56:31.533852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 81d92e8c-d72f-43e4-b2ba-0cab50f5eb79 · inbound

Principles and Practice of Deep Representation Learning: or a Mathematical Theory of Memory cites this paper.

Principles and Practice of Deep Representation Learning: or a Mathematical Theory of Memory Convergence of Learning Dynamics in Stackelberg Games

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T11:46:55.272247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.