Paper Citation Record · LEDGER

Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2102.08492.

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

pith.paper-citation-record.v1
2102.08492 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:06:17.765785Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T18:55:00.827329Z

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 4cc6e3a0-a54c-4803-91a9-6ba3571ffe9e · inbound

Online Poisoning Attack Against Reinforcement Learning under Black-box Environments cites this paper.

Online Poisoning Attack Against Reinforcement Learning under Black-box Environments Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T05:06:17.765785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa61771d-7a6a-453e-a35b-ecf44e911e0b · inbound

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

Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:25:20.406306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cf96c336-801e-4a6e-ba63-77ea8525a13a · inbound

When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs cites this paper.

When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T08:40:57.684718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fbc44274-4204-4dab-a59f-70ebe977c409 · inbound

Efficient Preference Poisoning Attack on Offline RLHF cites this paper.

Efficient Preference Poisoning Attack on Offline RLHF Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments

Reference 121

Resolution: verified exact; arxiv_id, observed 2026-05-09T05:50:27.125072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1c599e09-02d4-4472-98ea-ec7fa69dafad · 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 Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:23:16.750102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 37d4ac58-14f0-4ee4-b401-35797b8095b4 · 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 Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:55:00.828755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.