Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Bilevel reinforcement learning via the development of hyper-gradient without lower-level convexity
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.19697.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T11:26:02.922372Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T02:40:56.142800Z
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 74b5c409-7e4c-4513-a4f1-796fbb80ff35 · inbound
Penalty-Based First-Order Methods for Bilevel Optimization with Minimax and Constrained Lower-Level Problems cites this paper.
Penalty-Based First-Order Methods for Bilevel Optimization with Minimax and Constrained Lower-Level Problems Bilevel reinforcement learning via the development of hyper-gradient without lower-level convexity
Reference 71
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T02:40:56.147138Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d5f7b85f-c790-4f6b-be2c-172610441a12 · inbound
Efficient Hypergradient Descent for Inverse Reinforcement Learning cites this paper.
Efficient Hypergradient Descent for Inverse Reinforcement Learning Bilevel reinforcement learning via the development of hyper-gradient without lower-level convexity
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T11:26:02.922372Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.