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Paper Citation Record · LEDGER

Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2101.08452.

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

pith.paper-citation-record.v1
2101.08452 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:55:54.213230Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T18:55:00.845659Z

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 5b23fe12-f4b0-4877-b4f3-e0d6bae2dc9b · inbound

Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning cites this paper.

Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-23T03:25:20.324410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T03:24:33.788346Z digest=sha256:43d5db4bceacdcab19d99d12a30c2ac238dbe09376b0b1cc655ab81bfcdf707a

Observation b9ecdb87-ee50-4795-8257-fb15e3942fd9 · inbound

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning cites this paper.

ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T12:55:54.213230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:55:54.213230Z digest=sha256:d80a51974d9d106370cc7b6390c2ee561a16d2209ae5a638b455638be94caea9

Observation 92d01ebd-d99f-4d4e-b4d6-7d08a6ec9c91 · inbound

Collapsing Sequence-Level Data-Policy Coverage via Poisoning Attack in Offline Reinforcement Learning cites this paper.

Collapsing Sequence-Level Data-Policy Coverage via Poisoning Attack in Offline Reinforcement Learning Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T04:33:53.084260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:33:53.084260Z digest=sha256:633d93c75e85057441daaf7694313a0a9fa968c31bb4d7d31e2bdfda33a4bf78

Observation 4a1e4bdd-335c-4b95-8e03-7a2c428acd87 · inbound

RobustVLA: On Robustness of Vision-Language-Action Model against Multi-Modal Perturbations cites this paper.

RobustVLA: On Robustness of Vision-Language-Action Model against Multi-Modal Perturbations Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T14:58:38.134753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:58:38.134753Z digest=sha256:c6a91aaba4de094fd25dc3c3d74e5222a36589e7f2e0d3bbd0d220e622f8e243

Observation f0a8d32b-811c-4d43-9ab9-ed55a9dda75d · inbound

Robust Adversarial Policy Optimization Under Dynamics Uncertainty cites this paper.

Robust Adversarial Policy Optimization Under Dynamics Uncertainty Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:26:03.531757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T16:00:33.267264Z digest=sha256:c89970abfa08c6d5f2018dff1a7cc9a216190467b78a3311f8048b5f59a6bbf3

Observation f875dc7b-e0c2-40bf-9ae6-e4c9958a0a17 · 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 Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:00:36.007148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T19:13:15.234351Z digest=sha256:90ef9300264c05e635b08813879e74363c998fbef99d181e31f6c9a2e131ec63

Observation bffd33db-e0ce-4be6-9bbd-c7b382486855 · inbound

Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning cites this paper.

Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-20T12:23:16.766540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T12:23:11.320751Z digest=sha256:038fb1f1e6db4f5d67da7750c94c8c62bdc8ccf9742a431b459b24503becfb57

Observation 0bb7cb45-3bbb-4d9e-acfe-0be439c24d9b · inbound

Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning cites this paper.

Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-06-30T18:55:00.847104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T18:47:09.501908Z digest=sha256:e574bc05db4438d16a529880518720dc113bc160479cc6dff5268311101a1fd0

Observation 48e46889-b402-4026-ac6f-8a7378aa9857 · inbound

The Game Changer Problem: Controlling Equilibria with Discrete Rewards cites this paper.

The Game Changer Problem: Controlling Equilibria with Discrete Rewards Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Reference 141

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T08:24:26.391786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-30T08:20:47.028815Z digest=sha256:ff7517e3d1855d39189687fbe9f4be36a7b1a06c81f1150b5c4fa28ad87377e0