Paper Citation Record · LEDGER

Corrupted Learning Dynamics in Games

As of 14 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2412.07120.

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

pith.paper-citation-record.v1
2412.07120 v2

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:15:01.535254Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:28:50.780406Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T15:28:51.332886Z

Reference resolution

40 of 40 outbound references displayed

verified exact0
verified fuzzy29
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e22c8c24-cae6-4e00-abc9-a65db05b7942 · outbound

This paper cites Last-iterate convergence with full and noisy feedback in two-player zero-sum games.

Corrupted Learning Dynamics in Games Last-iterate convergence with full and noisy feedback in two-player zero-sum games

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:02.124464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7e21b46e-9503-4328-a669-eaeed8fbc295 · outbound

This paper cites Near-optimal no-regret learning for correlated equilibria in multi-player general-sum games.

Corrupted Learning Dynamics in Games Near-optimal no-regret learning for correlated equilibria in multi-player general-sum games

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:02.110945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 28e004f4-9acd-4e06-9d3a-9144dabb4ee8 · outbound

This paper cites Uncoupled learning dynamics with O( T) swap regret in multiplayer games.

Corrupted Learning Dynamics in Games Uncoupled learning dynamics with O( T) swap regret in multiplayer games

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:02.097991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d6b41d75-5868-40ba-9b19-85aa690b1392 · outbound

This paper cites On the convergence of no-regret learning dynamics in time-varying games.

Corrupted Learning Dynamics in Games On the convergence of no-regret learning dynamics in time-varying games

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:02.083975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 88eb826c-8b2b-49fa-8f65-696a3ec72b9f · outbound

This paper cites An adaptive mirror-prox method for variational inequalities with singular operators.

Corrupted Learning Dynamics in Games An adaptive mirror-prox method for variational inequalities with singular operators

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:02.070039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1748802c-6c4b-44c0-b7c0-802310a864ba · outbound

This paper cites Adaptive extra-gradient methods for min-max optimization and games.

Corrupted Learning Dynamics in Games Adaptive extra-gradient methods for min-max optimization and games

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:02.057980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a2ba2418-a76d-4bef-a19e-d27fd9d0527f · outbound

This paper cites an unresolved cited work.

Corrupted Learning Dynamics in Games Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T19:15:01.363214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48e13c73-404b-4309-a880-4828730ee2c3 · outbound

This paper cites From external to internal regret.

Corrupted Learning Dynamics in Games From external to internal regret

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T19:15:01.366517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6477d712-4c79-460c-abc0-10f98efef257 · outbound

This paper cites Prediction, learning, and games.

Corrupted Learning Dynamics in Games Prediction, learning, and games

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T19:15:01.370539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9105f036-1c5e-4c20-b92b-4edb4a21ce0a · outbound

This paper cites Hedging in games: Faster convergence of external and swap regrets.

Corrupted Learning Dynamics in Games Hedging in games: Faster convergence of external and swap regrets

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:02.018028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8c02879f-9db4-4f10-8794-fdb2d25ad86e · outbound

This paper cites Learning with bandit feedback in potential games.

Corrupted Learning Dynamics in Games Learning with bandit feedback in potential games

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:02.005058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0b7ee422-2a2e-4b89-8aac-313cae9ffa9b · outbound

This paper cites From external to swap regret 2.0: An efficient reduction for large action spaces.

Corrupted Learning Dynamics in Games From external to swap regret 2.0: An efficient reduction for large action spaces

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.990740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b4aaf92d-cfcd-4553-9359-8dcd581bc371 · outbound

This paper cites Near-optimal no-regret algorithms for zero-sum games.

Corrupted Learning Dynamics in Games Near-optimal no-regret algorithms for zero-sum games

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.975623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 488efd3f-5dc7-43ed-9a42-e95139c9c518 · outbound

This paper cites Near-optimal no-regret learning in general games.

Corrupted Learning Dynamics in Games Near-optimal no-regret learning in general games

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.961911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f0f97d45-a173-4c37-9bde-f91b3efb6af1 · outbound

This paper cites Near-optimal no-regret learning dynamics for general convex games.

Corrupted Learning Dynamics in Games Near-optimal no-regret learning dynamics for general convex games

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.948038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a00101af-e242-4fe2-a94d-4e8fa4a4870f · outbound

This paper cites On the last-iterate convergence in time-varying zero-sum games: Extra gradient succeeds where optimism fails.

Corrupted Learning Dynamics in Games On the last-iterate convergence in time-varying zero-sum games: Extra gradient succeeds where optimism fails

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.925891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1372b58e-e970-4002-b334-dcb9781d21e5 · outbound

This paper cites Foster and Rakesh V.

Corrupted Learning Dynamics in Games Foster and Rakesh V

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.907982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 59d3258b-a9f3-4874-838b-725d3df460e8 · outbound

This paper cites Learning in games: Robustness of fast convergence.

Corrupted Learning Dynamics in Games Learning in games: Robustness of fast convergence

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.887874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d4a27140-848f-4bfa-938e-ac26c992ef52 · outbound

This paper cites A decision-theoretic generalization of on-line learning and an application to boosting.

Corrupted Learning Dynamics in Games A decision-theoretic generalization of on-line learning and an application to boosting

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T19:15:01.416516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 764679fc-a4ac-484f-b7bc-ac5b273dbb70 · outbound

This paper cites Schapire.

Corrupted Learning Dynamics in Games Schapire

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.864523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f172b9a5-344d-4a08-93da-7c91364f7d0c · outbound

This paper cites Bayes correlated equilibria, no-regret dynamics in Bayesian games, and the price of anarchy.

Corrupted Learning Dynamics in Games Bayes correlated equilibria, no-regret dynamics in Bayesian games, and the price of anarchy

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T19:15:01.424764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ed6b981-1fab-452a-9609-b692aec6f684 · outbound

This paper cites Meta-learning in games.

Corrupted Learning Dynamics in Games Meta-learning in games

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.846419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 694f34f9-e0fb-44cf-a286-11665415b481 · outbound

This paper cites A simple adaptive procedure leading to correlated equilibrium.

Corrupted Learning Dynamics in Games A simple adaptive procedure leading to correlated equilibrium

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T19:15:01.433529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9247b8c8-0bba-4614-8a06-cef986f08651 · outbound

This paper cites Introduction to online convex optimization.

Corrupted Learning Dynamics in Games Introduction to online convex optimization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T19:15:01.437665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05318fdb-b04b-4fdc-b692-23c466ac8c31 · outbound

This paper cites Adaptive learning in continuous games: Optimal regret bounds and convergence to Nash equilibrium.

Corrupted Learning Dynamics in Games Adaptive learning in continuous games: Optimal regret bounds and convergence to Nash equilibrium

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.799173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0249ed30-b819-4320-bfbd-ef34d91dcf1c · outbound

This paper cites No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation.

Corrupted Learning Dynamics in Games No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.784915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d0d9f54f-fc86-4c9b-b465-161eed89e003 · outbound

This paper cites Let's be honest: An optimal no-regret framework for zero-sum games.

Corrupted Learning Dynamics in Games Let's be honest: An optimal no-regret framework for zero-sum games

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.770261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation eaa47582-9454-4699-9c98-64f9198a39c6 · outbound

This paper cites Finite-time last-iterate convergence for multi-agent learning in games.

Corrupted Learning Dynamics in Games Finite-time last-iterate convergence for multi-agent learning in games

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.752422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b9156325-8b27-4163-a63b-f9fbe497cd92 · outbound

This paper cites The weighted majority algorithm.

Corrupted Learning Dynamics in Games The weighted majority algorithm

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T19:15:01.481915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bc675b3-d5ac-4e2c-bd58-ef8cc3e3c064 · outbound

This paper cites Interior-point methods for optimization.

Corrupted Learning Dynamics in Games Interior-point methods for optimization

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.727228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 82758398-c3f5-4c4e-babb-bcc18feb600e · outbound

This paper cites Interior-Point Polynomial Algorithms in Convex Programming.

Corrupted Learning Dynamics in Games Interior-Point Polynomial Algorithms in Convex Programming

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.711225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 50754aaa-29ea-4d62-b0d2-5cb876a73b2b · outbound

This paper cites Online Learning: A Modern Introduction Using Convex Optimization.

Corrupted Learning Dynamics in Games Online Learning: A Modern Introduction Using Convex Optimization

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T19:15:01.494875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a8f5238-aabd-47bd-896c-9e8c1f0af4f3 · outbound

This paper cites Optimal Non-Asymptotic Lower Bound on the Minimax Regret of Learning with Expert Advice.

Corrupted Learning Dynamics in Games Optimal Non-Asymptotic Lower Bound on the Minimax Regret of Learning with Expert Advice

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T19:15:01.498800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bda0b04-97df-455e-a3f2-706396df5236 · outbound

This paper cites Fast swap regret minimization and applications to approximate correlated equilibria.

Corrupted Learning Dynamics in Games Fast swap regret minimization and applications to approximate correlated equilibria

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.695172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a7796686-6dff-4718-8938-94d673d2066d · outbound

This paper cites Online learning with predictable sequences.

Corrupted Learning Dynamics in Games Online learning with predictable sequences

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T19:15:01.508577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ea3e2ca-a296-481a-b134-af8cafa91d99 · outbound

This paper cites Optimization, learning, and games with predictable sequences.

Corrupted Learning Dynamics in Games Optimization, learning, and games with predictable sequences

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.671034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f1c33c40-e1b8-46e9-86c2-1dc1ee75910a · outbound

This paper cites Fast convergence of regularized learning in games.

Corrupted Learning Dynamics in Games Fast convergence of regularized learning in games

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.658795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4d141ac0-c841-4a22-9e85-c7fd96151e2c · outbound

This paper cites More adaptive algorithms for adversarial bandits.

Corrupted Learning Dynamics in Games More adaptive algorithms for adversarial bandits

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.647581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 34829585-5cca-4eeb-a28a-6f87f1237701 · outbound

This paper cites Fast rates in time-varying strongly monotone games.

Corrupted Learning Dynamics in Games Fast rates in time-varying strongly monotone games

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.632841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3787341b-a57f-4223-a8c0-2b3f0474afe3 · outbound

This paper cites No-regret learning in time-varying zero-sum games.

Corrupted Learning Dynamics in Games No-regret learning in time-varying zero-sum games

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:15:01.618732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation d158c1b7-9621-4ec8-a8eb-6cd808474cdd · inbound

Pointwise Convergence in Games with Conflicting Interest cites this paper.

Pointwise Convergence in Games with Conflicting Interest Corrupted Learning Dynamics in Games

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:28:51.439271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.