Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Poisoning Deep Reinforcement Learning Agents with In-Distribution Triggers
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2106.07798.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:30:14.112573Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T19:16:00.601482Z
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 882e177c-637c-4247-97da-c399b55881a8 · inbound
BLAST: A Stealthy Backdoor Leverage Attack against Cooperative Multi-Agent Deep Reinforcement Learning based Systems cites this paper.
BLAST: A Stealthy Backdoor Leverage Attack against Cooperative Multi-Agent Deep Reinforcement Learning based Systems Poisoning Deep Reinforcement Learning Agents with In-Distribution Triggers
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:30:14.112573Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation da0798f3-51ad-4443-a5ed-083a64caa3db · inbound
Beyond Training-time Poisoning: Component-level and Post-training Backdoors in Deep Reinforcement Learning cites this paper.
Beyond Training-time Poisoning: Component-level and Post-training Backdoors in Deep Reinforcement Learning Poisoning Deep Reinforcement Learning Agents with In-Distribution Triggers
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:47:32.478998Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7c2c57c-0884-4678-a95a-3527c2bc3779 · inbound
Auditing Near-Optimal Policies Can Be Exponentially Hard: Conditional Query Lower Bounds via Occupancy Rashomon Capacity cites this paper.
Auditing Near-Optimal Policies Can Be Exponentially Hard: Conditional Query Lower Bounds via Occupancy Rashomon Capacity Poisoning Deep Reinforcement Learning Agents with In-Distribution Triggers
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T19:16:00.603264Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.