Paper Citation Record · LEDGER

Soft Policy Optimization: Online Off-Policy RL for Sequence Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2503.05453.

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

pith.paper-citation-record.v1
2503.05453 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:53:37.298177Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:38:39.798357Z

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 1165ba8d-9c0c-44ee-84a0-a7fdd4724392 · inbound

On a few pitfalls in KL divergence gradient estimation for RL cites this paper.

On a few pitfalls in KL divergence gradient estimation for RL Soft Policy Optimization: Online Off-Policy RL for Sequence Models

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T04:53:37.298177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ea8bd9b-b671-4073-ae7e-c9bc97ee0670 · inbound

Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model cites this paper.

Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model Soft Policy Optimization: Online Off-Policy RL for Sequence Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T18:57:38.598767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 608546d8-fa54-45c1-849a-634703479de5 · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models Soft Policy Optimization: Online Off-Policy RL for Sequence Models

Reference 94

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:02:25.202577Z

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 3b68c779-f96a-425a-b684-4d6ac6e24401 · inbound

Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning cites this paper.

Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning Soft Policy Optimization: Online Off-Policy RL for Sequence Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:15:49.269860Z

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 a7f948ee-2452-4b7c-904e-9b872461beca · inbound

DecompRL: Solving Harder Problems by Learning Modular Code Generation cites this paper.

DecompRL: Solving Harder Problems by Learning Modular Code Generation Soft Policy Optimization: Online Off-Policy RL for Sequence Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-03T16:38:39.799985Z

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 7af6fc46-1954-4942-8143-252a77b4678c · inbound

Mask-Aware Policy Gradients for Diffusion Language Models cites this paper.

Mask-Aware Policy Gradients for Diffusion Language Models Soft Policy Optimization: Online Off-Policy RL for Sequence Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T23:55:55.239723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.