Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T16:19:43.471104Z
Paper Citation Record · LEDGER
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training
As of 9 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 1 inbound Pith citation observation for arXiv:2507.13833.
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 2026-08-04T16:07:43.491850Z
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
8 of 8 outbound references displayed
- verified exact0
- verified fuzzy1
- unresolved6
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 84f5e258-d93c-420f-85ec-e0966016eae1 · outbound
This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:19:43.447887Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation abdb7607-10b1-4350-b021-82654c4ba76e · outbound
This paper cites MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning.
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:19:43.455599Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5f5cb8a5-aee6-49bc-aba0-684a86abf0af · outbound
This paper cites Accessed: 2025-09-17.
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training Accessed: 2025-09-17
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:19:43.715378Z
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 2e46e0af-e552-45fa-a0f8-ae73cf09750c · outbound
This paper cites Laminar: A scalable asynchronous rl post-training framework, 2025a.
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training Laminar: A scalable asynchronous rl post-training framework, 2025a
Reference 8
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-06T16:19:43.471104Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1ac9c838-70c1-4125-a86a-e59b50114845 · outbound
This paper cites ISBN 9781450379984.
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training ISBN 9781450379984
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:19:43.463844Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2bf3ee51-b65c-4289-b049-862bb2e7007c · outbound
This paper cites NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment.
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training NeMo-Aligner: Scalable Toolkit for Efficient Model Alignment
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:19:43.466905Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 03a7ba04-d454-4284-9139-2006f9635168 · outbound
This paper cites an unresolved cited work.
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training Unresolved cited work
Reference 2025
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T16:19:43.727121Z
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 a312c340-edbd-4b37-9f81-0118ae159be5 · outbound
This paper cites OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework.
DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework
Reference 2026
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:19:43.451559Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation f261017e-8295-440b-8296-4b979df7e659 · 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 DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training
Reference 193
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:07:43.491850Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.