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Paper Citation Record · LEDGER

Adding Conditional Control to Diffusion Models with Reinforcement Learning

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.12120.

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

pith.paper-citation-record.v1
2406.12120 v3

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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:06:05.605157Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T12:46:04.052927Z

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 f3511787-1050-4708-9488-ff946b21a301 · inbound

Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence cites this paper.

Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence Adding Conditional Control to Diffusion Models with Reinforcement Learning

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:05.605157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:06:05.605157Z digest=sha256:64d02b441e8acb1405c204b098b5140b8b04bf65378f46aeb973a6d401511f1c

Observation ec129f1b-8320-45eb-8131-ef7ac8438137 · inbound

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training cites this paper.

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training Adding Conditional Control to Diffusion Models with Reinforcement Learning

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:46:04.065852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-10T03:04:54.146481Z digest=sha256:d25d873a61991b80b314c63f6b5e2af93d33b8c9a30205002a0720cb501444f8