Paper Citation Record · LEDGER

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning

As of 15 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 5 inbound Pith citation observations for arXiv:2502.01819.

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

pith.paper-citation-record.v1
2502.01819 v3

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:29:12.477304Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:44:36.837980Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T18:38:53.000576Z

Reference resolution

35 of 35 outbound references displayed

verified exact1
verified fuzzy3
unresolved30
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9ad45e5c-fefb-4c69-b1fe-a6645a2c7d85 · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Training Diffusion Models with Reinforcement Learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:11.815314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8908ba33-e341-4015-9331-03746b77f918 · outbound

This paper cites Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:11.949366Z

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Unavailable: canonical work link unavailable.

Observation 6e0fa41b-a1e7-49e7-9910-ac1c14611548 · outbound

This paper cites Optimizing DDPM Sampling with Shortcut Fine-Tuning.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Optimizing DDPM Sampling with Shortcut Fine-Tuning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.102481Z

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Observation 9d31d82f-5625-46b9-8dbc-719afcb9dcc9 · outbound

This paper cites DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.106970Z

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Observation 7b140705-6248-492b-a55b-9936f0285c30 · outbound

This paper cites Reward-Directed Score-Based Diffusion Models via q-Learning.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Reward-Directed Score-Based Diffusion Models via q-Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.111582Z

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Observation 8c78c11f-a17a-4084-bb14-1053003b7e95 · outbound

This paper cites Optimizing Prompts for Text-to-Image Generation.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Optimizing Prompts for Text-to-Image Generation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.116193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 318bb216-e0e6-40c9-ab84-9732adb0c691 · outbound

This paper cites an unresolved cited work.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-09T14:29:13.477786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 188b076e-de43-4217-8cb8-be549dd71121 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.137957Z

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Unavailable: canonical work link unavailable.

Observation bd203227-8bd3-4fd9-a681-d2e6ad307b98 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.142340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13bba21e-6c31-49c1-a0a5-6c9196c3db35 · outbound

This paper cites Diffusion Policy Policy Optimization.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Diffusion Policy Policy Optimization

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.146870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b655a89a-93fb-4e3d-840d-8e4b5978885c · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Progressive Distillation for Fast Sampling of Diffusion Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.151666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1e74cfb-e291-45f9-a336-5b54ba8f2d88 · outbound

This paper cites Improving Image Captioning with Better Use of Captions.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Improving Image Captioning with Better Use of Captions

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.282159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cefcffbe-160d-4714-8c1b-bc54d8e64a5e · outbound

This paper cites Denoising Diffusion Implicit Models.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Denoising Diffusion Implicit Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.359251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2eed287d-df1d-4f4f-b63e-981d1047143d · outbound

This paper cites Solving Inverse Problems in Medical Imaging with Score-Based Generative Models.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Solving Inverse Problems in Medical Imaging with Score-Based Generative Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.412419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 547aceb9-289b-4e0c-8fd9-df5eac3c48b9 · outbound

This paper cites Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.423240Z

Source-reported events for the cited work

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Observation 68fbedcb-4df2-4a7d-8e21-43ba93e5d1a7 · outbound

This paper cites Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.427168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71d5a541-b706-4bb9-9431-0d7e780f0a85 · outbound

This paper cites Preference Tuning with Human Feedback on Language, Speech, and Vision Tasks: A Survey.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Preference Tuning with Human Feedback on Language, Speech, and Vision Tasks: A Survey

Reference 26

Resolution: metadata mismatch; local_arxiv, observed 2026-08-09T14:29:12.924859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 155c2cbe-35a1-495b-9c67-dcdddbc2b032 · outbound

This paper cites GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.435649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a7f53eb-6642-4d76-9d21-89c598da81b0 · outbound

This paper cites Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-09T14:29:12.769275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 00abb90a-3f36-4d01-a015-2da311d0e575 · outbound

This paper cites Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generation.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.444589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6625498d-78cf-4fa1-9122-0b04808df995 · outbound

This paper cites Fast Sampling of Diffusion Models with Exponential Integrator.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Fast Sampling of Diffusion Models with Exponential Integrator

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.448838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6e1ead3-d69c-4063-80ae-077782e590de · outbound

This paper cites gDDIM: Generalized denoising diffusion implicit models.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning gDDIM: Generalized denoising diffusion implicit models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.454146Z

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Unavailable: canonical work link unavailable.

Observation c27a3190-1fc2-4762-aa19-1da2beda719d · outbound

This paper cites Scores as Actions: a framework of fine-tuning diffusion models by continuous-time reinforcement learning.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Scores as Actions: a framework of fine-tuning diffusion models by continuous-time reinforcement learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.459033Z

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Observation fd453468-5b45-4d12-9523-fdef139f399e · outbound

This paper cites predicted x0.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning predicted x0

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:29:13.463637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 561c8ab2-6f62-410f-9e1a-749fb9e94e0b · outbound

This paper cites predicted x0.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning predicted x0

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:29:13.447926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c14b68ca-c56b-414b-8899-dbbe163014b8 · outbound

This paper cites We adopt two ways of derivations: (a) Notice that, if we treat the ˆxθ (t, Xt) as a constant in (38) (or assume that it does not change w.r.p.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning We adopt two ways of derivations: (a) Notice that, if we treat the ˆxθ (t, Xt) as a constant in (38) (or assume that it does not change w.r.p

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:29:13.432515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 23460e6b-4a91-4898-9901-f3cdde308fc1 · outbound

This paper cites Fine-tuning of diffusion models via stochastic control: entropy regularization and beyond.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Fine-tuning of diffusion models via stochastic control: entropy regularization and beyond

Reference 1999

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.419252Z

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Observation 99790938-35c3-4b29-af97-657a3b53ebff · outbound

This paper cites Aligning Text-to-Image Models using Human Feedback.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Aligning Text-to-Image Models using Human Feedback

Reference 2009

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.133392Z

Source-reported events for the cited work

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Observation f003bc6f-d8b6-4a98-aeef-f1bde2c43243 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.192879Z

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Observation 198a0a69-340c-42b8-8ad4-d38c508af818 · outbound

This paper cites Directly Fine-Tuning Diffusion Models on Differentiable Rewards.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Directly Fine-Tuning Diffusion Models on Differentiable Rewards

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.019456Z

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Observation 5097f194-b6d8-435f-a81e-d766c142c8af · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Imagen Video: High Definition Video Generation with Diffusion Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.120433Z

Source-reported events for the cited work

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Observation d922e02d-ad8e-4824-bfa9-30962aeefab4 · outbound

This paper cites Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.091436Z

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Observation 9aa508f7-2248-432b-b9c5-1b476b2cb3ea · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning LoRA: Low-Rank Adaptation of Large Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.125068Z

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Observation 27a024c8-43f9-48a7-85ab-26a0c86d5cb3 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:11.879830Z

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Observation 8082898e-1517-48f2-a77b-5a873d46bf2d · outbound

This paper cites Scaling Rectified Flow Transformers for High-Resolution Image Synthesis.

Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning Scaling Rectified Flow Transformers for High-Resolution Image Synthesis

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-09T14:29:12.096528Z

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Pith citing papers

Observation 4e45631e-d946-4b7a-b80d-c6d1cbbcb9e7 · inbound

Flow-GRPO: Training Flow Matching Models via Online RL cites this paper.

Flow-GRPO: Training Flow Matching Models via Online RL Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T18:45:16.728520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6829bc90-f340-4ee5-89d3-ea9de10cd911 · inbound

Is RL fine-tuning harder than regression? A PDE learning approach for diffusion models cites this paper.

Is RL fine-tuning harder than regression? A PDE learning approach for diffusion models Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T16:44:36.837980Z

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Observation 6c6aee69-8f73-4a82-999d-d86651382aeb · inbound

Improving Text-to-Image Generation with Intrinsic Self-Confidence Rewards cites this paper.

Improving Text-to-Image Generation with Intrinsic Self-Confidence Rewards Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning

Reference 89

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T18:41:28.922983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 24c327ab-edde-46d3-8a47-fe166e38ee92 · inbound

Energy Generative Modeling: A Lyapunov-based Energy Matching Perspective cites this paper.

Energy Generative Modeling: A Lyapunov-based Energy Matching Perspective Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T16:36:08.216028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0e4474a6-2ce3-46b3-9e89-59faa507c1ae · inbound

Embedding-perturbed Exploration Preference Optimization for Flow Models cites this paper.

Embedding-perturbed Exploration Preference Optimization for Flow Models Score as Action: Fine-Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning

Reference 97

Resolution: verified exact; arxiv_id, observed 2026-05-20T18:38:53.002168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.