Paper Citation Record · LEDGER

LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2505.24034.

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

pith.paper-citation-record.v1
2505.24034 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:19:26.241394Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e74338b5-eb36-4ba3-884a-ddd1729123f4 · inbound

Reinforcement Learning from Human Feedback cites this paper.

Reinforcement Learning from Human Feedback LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 133

Resolution: verified exact; arxiv_id, observed 2026-05-22T19:32:01.297713Z

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 62aa2849-4bc7-4bce-953f-b36661f1c2ce · inbound

Magistral cites this paper.

Magistral LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T04:19:26.241394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77243c07-76f2-453d-878e-2288b1fa8aa7 · inbound

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle cites this paper.

Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 200

Resolution: unresolved; no resolver link, observed 2026-08-04T16:07:43.979849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 317ba9ef-ed90-4c32-8c98-33dd0c7d27ea · inbound

HetRL: Efficient Reinforcement Learning for LLMs in Heterogeneous Environments cites this paper.

HetRL: Efficient Reinforcement Learning for LLMs in Heterogeneous Environments LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:23:36.641772Z

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 4e20ecf2-a14a-4eec-9edc-ab8728858d75 · 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 LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-04T06:25:54.516468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee4ba978-e8d1-489f-b615-3c4137c3991b · inbound

TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training cites this paper.

TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:11:00.631266Z

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 e6ba9bdf-05e5-4cc8-8ccf-873d988d8145 · 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 LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:46:26.425646Z

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 3521626d-9bfb-47d7-924e-d54365baccd4 · inbound

When to Stop Reusing: Dynamic Gradient Gating for Sample-Efficient RLVR cites this paper.

When to Stop Reusing: Dynamic Gradient Gating for Sample-Efficient RLVR LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:33:07.364766Z

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 3ca7aa93-bd09-4601-9abd-9e0159acd6aa · inbound

Spend Your Rollouts Where It Counts: Rollout Allocation for Group-Based RL Post-Training cites this paper.

Spend Your Rollouts Where It Counts: Rollout Allocation for Group-Based RL Post-Training LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-06-29T19:53:55.792604Z

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 cda6d2b5-4d4e-4fcb-9c45-e253884a7721 · inbound

Libra: Efficient Resource Management for Agentic RL Post-Training cites this paper.

Libra: Efficient Resource Management for Agentic RL Post-Training LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:16:27.151232Z

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 1a77efd9-f915-4fbb-b87c-7876560eb8d5 · inbound

Rollout-Level Advantage-Prioritized Experience Replay for GRPO cites this paper.

Rollout-Level Advantage-Prioritized Experience Replay for GRPO LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-07-02T06:06:41.077555Z

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 9394f3ea-be4d-41d8-a70f-3022c8445dcc · inbound

AsyncWebRL: Efficient Multi-Step RL for Visual Web Agents cites this paper.

AsyncWebRL: Efficient Multi-Step RL for Visual Web Agents LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T11:56:55.543867Z

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 2f99b87d-9796-49cc-ab6b-9a492c5824bc · inbound

Sparrow: Sparse Rollout for Stable and Efficient Long-context RL of Large Language Models cites this paper.

Sparrow: Sparse Rollout for Stable and Efficient Long-context RL of Large Language Models LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:07:26.505309Z

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 a9cd52f0-5201-422d-9aed-8d6667281aaa · inbound

Harnessing Routing Foresight for Micro-step-level MoE load balancing in RL Post-training cites this paper.

Harnessing Routing Foresight for Micro-step-level MoE load balancing in RL Post-training LlamaRL: A Distributed Asynchronous Reinforcement Learning Framework for Efficient Large-scale LLM Training

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-07-03T12:58:08.711158Z

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.