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Paper Citation Record · LEDGER

Fine-Tuning Language Models with Reward Learning on Policy

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.19279.

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

pith.paper-citation-record.v1
2403.19279 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:24:29.885002Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T16:38:37.065338Z

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 f0950b69-1412-4337-8094-aad210ce9b44 · inbound

Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy cites this paper.

Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy Fine-Tuning Language Models with Reward Learning on Policy

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-07T13:24:29.885002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:24:29.885002Z digest=sha256:269b700b24daacf988124c096b8a7a8b1082610814eac1aa91f88cba956b5ff9

Observation 40bb854f-01ac-48bd-aa67-351e05df5eba · inbound

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning cites this paper.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Fine-Tuning Language Models with Reward Learning on Policy

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:38:37.143823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-06T16:38:32.272467Z digest=sha256:796cacb613dcaf18cb0ec13c51302d05c9b9615f47c3cc042a5e18fda6d903c9