Paper Citation Record · LEDGER

Polar: Agentic RL on Any Harness at Scale

As of 18 August 2026, this Paper Citation Record lists 3 of 3 outbound references and 2 inbound Pith citation observations for arXiv:2605.24220.

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

pith.paper-citation-record.v1
2605.24220 v1

Coverage vector

measured 3 of 3 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T14:38:14.073340Z

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T09:49:30.880046Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

3 of 3 outbound references displayed

verified exact3
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f82ad98-72d6-4823-a9ae-1afa269f3cf0 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Polar: Agentic RL on Any Harness at Scale DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-06-30T14:44:45.317100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 68348981-15e8-439f-8544-a3e06f6893d9 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Polar: Agentic RL on Any Harness at Scale DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-06-30T14:44:45.314693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b9652e40-f9f6-4e5d-8a82-71ac2f4f709e · outbound

This paper cites SGLang: Efficient Execution of Structured Language Model Programs.

Polar: Agentic RL on Any Harness at Scale SGLang: Efficient Execution of Structured Language Model Programs

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-06-30T14:44:45.311780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation 43f42677-c62b-41eb-8f52-a20329e534ab · inbound

OpenForgeRL: Train Harness-native Agents in Any Environment cites this paper.

OpenForgeRL: Train Harness-native Agents in Any Environment Polar: Agentic RL on Any Harness at Scale

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T07:08:40.241133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b21a729-fd86-4cf5-b580-1adf8cc3ca45 · inbound

Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning cites this paper.

Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning Polar: Agentic RL on Any Harness at Scale

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-01T09:49:30.880046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.