Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
REBEL: Reinforcement Learning via Regressing Relative Rewards
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2404.16767.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:44:57.195037Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T04:45:54.895043Z
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 47c6f8f3-e850-427d-a039-f2b44a779a37 · inbound
Square$\chi$PO: Differentially Private and Robust $\chi^2$-Preference Optimization in Offline Direct Alignment cites this paper.
Square$\chi$PO: Differentially Private and Robust $\chi^2$-Preference Optimization in Offline Direct Alignment REBEL: Reinforcement Learning via Regressing Relative Rewards
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:44:57.195037Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bd99eeb9-8d0e-4a3d-9310-02ab785e3886 · inbound
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges cites this paper.
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges REBEL: Reinforcement Learning via Regressing Relative Rewards
Reference 234
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:13:07.149419Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bdb3b2cc-ab36-4992-85e8-d20e70146954 · inbound
On the Sample Complexity of Differentially Private Policy Optimization cites this paper.
On the Sample Complexity of Differentially Private Policy Optimization REBEL: Reinforcement Learning via Regressing Relative Rewards
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T04:45:54.898298Z
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.
Observation 64401bb4-50c1-4284-9ba8-529ec5fdd178 · inbound
Target Policy Optimization cites this paper.
Target Policy Optimization REBEL: Reinforcement Learning via Regressing Relative Rewards
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:05:48.547299Z
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.
Observation ba279caa-04cb-408f-aeca-b17a6485f1ba · inbound
Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.
Multi-Turn On-Policy Distillation with Prefix Replay REBEL: Reinforcement Learning via Regressing Relative Rewards
Reference 72
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T13:53:36.775836Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 053ca9e2-88b8-4a03-8e0f-f300343c83cb · inbound
Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.
Multi-Turn On-Policy Distillation with Prefix Replay REBEL: Reinforcement Learning via Regressing Relative Rewards
Reference 73
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T08:40:39.691665Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.