Paper Citation Record · LEDGER

An Adaptive Placement and Parallelism Framework for Accelerating RLHF Training

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2312.11819.

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

pith.paper-citation-record.v1
2312.11819 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:45:29.683650Z

measured 0 of 1 external citation measurements

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 2026-08-18T06:34:40.430872+00:00.

Observation 9bb2f068-38ab-4814-b125-249b1d0199b6 · inbound

LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training cites this paper.

LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training An Adaptive Placement and Parallelism Framework for Accelerating RLHF Training

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:29.683650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-18T06:34:40.430872+00:00.