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Paper Citation Record · LEDGER

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

As of 21 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 2026-08-21T06:32:19.484+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.

source=pdf_text observed=2026-08-07T04:53:37.298177Z digest=sha256:6d104eb9cf029496942b72f50d9cd02e6264795f574bfc25b5d4d0d47ca1b37a

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.

source=arxiv_source observed=2026-08-06T18:57:38.598767Z digest=sha256:e4b83068160da051459d6df40c7464cc6af41b547d0f2f688fdce2713f5a61aa

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-18T00:02:24.352947Z digest=sha256:2087ae2f0cdd02ebdbec915fa41f073932eed9f1ea2fc13ca551ec4d970d159a

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-10T19:15:27.406778Z digest=sha256:b29886a18899fba13a5b8203f42254996910b3ab1ce2f6a384b194d36f53614b

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 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-07-03T16:30:34.793328Z digest=sha256:d9a55f01b39e889f726e3182cdb4b067fdf35d91e135329a5d97407736d175ea

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.

source=pdf_text observed=2026-08-01T23:55:55.239723Z digest=sha256:ae6e5e262b158ef4a5083943a6e0eaa811c30178f321242e9ac8dfecee808290