Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
An Adaptive Placement and Parallelism Framework for Accelerating RLHF Training
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2312.11819.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T06:25:54.634282Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T08:46:26.348093Z
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 8d1ac14e-4817-499c-85d6-d392bc0ec37a · inbound
HybridFlow: A Flexible and Efficient RLHF Framework cites this paper.
HybridFlow: A Flexible and Efficient RLHF Framework An Adaptive Placement and Parallelism Framework for Accelerating RLHF Training
Reference 92
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:53:38.938972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1ea59b38-0d3e-4802-8a51-36cf7a286158 · inbound
StaleFlow: Staleness-Aware Data Management for Mitigating Data Skewness in Fully Disaggregated RL Post-Training cites this paper.
StaleFlow: Staleness-Aware Data Management for Mitigating Data Skewness in Fully Disaggregated RL Post-Training An Adaptive Placement and Parallelism Framework for Accelerating RLHF Training
Reference 77
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T06:25:54.634282Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a0811e86-f064-456e-8918-7f082b979b15 · inbound
DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training cites this paper.
DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training An Adaptive Placement and Parallelism Framework for Accelerating RLHF Training
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T08:46:26.352121Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.