Paper Citation Record · LEDGER

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment

As of 8 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 2 inbound Pith citation observations for arXiv:2506.02221.

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

pith.paper-citation-record.v1
2506.02221 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:34:06.057829Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T05:35:48.896721Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T10:25:41.145492Z

Reference resolution

68 of 68 outbound references displayed

verified exact0
verified fuzzy37
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4c884881-ca4a-4c4a-b7a2-c16487079f9f · outbound

This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

Reference 1

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Observation 09f73fc6-c10a-408d-96ee-5763796ad1a5 · outbound

This paper cites Lora learns less and forgets less.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Lora learns less and forgets less

Reference 2

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Observation c6bfefd8-8e32-4699-b119-e06682f1ac7e · outbound

This paper cites Align your latents: High-resolution video synthesis with la- tent diffusion models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Align your latents: High-resolution video synthesis with la- tent diffusion models

Reference 3

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Observation 24483d94-5ec4-48be-afe0-e669d2009361 · outbound

This paper cites Vir- tual kitti 2, 2020.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Vir- tual kitti 2, 2020

Reference 4

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Observation ffc2993e-3895-4bdd-b35f-6aa6d17f41e3 · outbound

This paper cites Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner

Reference 5

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Observation 3893c0ab-624b-4fb3-9fa7-6c360ff1166d · outbound

This paper cites Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

Reference 6

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Observation ed575bf2-ea23-4aaa-b78b-9c3f66bfe943 · outbound

This paper cites Generative Models: What Do They Know? Do They Know Things? Let's Find Out!.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Generative Models: What Do They Know? Do They Know Things? Let's Find Out!

Reference 7

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Observation 06706ecd-5d37-42f6-ac4a-c63adb71ee98 · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 8

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Observation 90a15785-eee4-4375-baf7-1765d3c82d9d · outbound

This paper cites Geowiz- ard: Unleashing the diffusion priors for 3d geometry estima- tion from a single image.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Geowiz- ard: Unleashing the diffusion priors for 3d geometry estima- tion from a single image

Reference 9

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Observation 0d733709-b4b8-4a50-8da9-47e6f88a046f · outbound

This paper cites Diffusion Models and Representation Learning: A Survey.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Diffusion Models and Representation Learning: A Survey

Reference 10

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Observation 566b0b82-812c-4702-b9b3-746829ef90fe · outbound

This paper cites Distillation of diffusion features for semantic correspondence.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Distillation of diffusion features for semantic correspondence

Reference 11

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Observation 041b8f47-16d5-4425-8dfc-5107e5f5f772 · outbound

This paper cites Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models

Reference 12

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Observation 955ad597-ed1a-4109-99d3-a508a3e85145 · outbound

This paper cites Vision meets robotics: The kitti dataset.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Vision meets robotics: The kitti dataset

Reference 13

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Observation ef40478a-da26-4d50-8a52-055132e27f34 · outbound

This paper cites Depthfm: Fast monocular depth estimation with flow matching.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Depthfm: Fast monocular depth estimation with flow matching

Reference 14

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Observation 46b866d4-f5a1-4184-9df7-2f40c0b3dfda · outbound

This paper cites Animatediff: Animate your personalized text-to- image diffusion models without specific tuning.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Animatediff: Animate your personalized text-to- image diffusion models without specific tuning

Reference 15

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Observation 30127671-5022-4262-aebe-6db07d384c1d · outbound

This paper cites Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction

Reference 16

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Observation 055273bd-b2c2-4752-967b-2ccf86bf6c2a · outbound

This paper cites Scalecrafter: Tuning-free higher- resolution visual generation with diffusion models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Scalecrafter: Tuning-free higher- resolution visual generation with diffusion models

Reference 17

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Observation 14b2b457-1036-49ed-9538-63bbf83bb551 · outbound

This paper cites Classifier-free diffusion guidance.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Classifier-free diffusion guidance

Reference 18

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Observation ce8f5b7a-f7fa-4d9c-a7d4-fa17f89f0648 · outbound

This paper cites Denoising dif- fusion probabilistic models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Denoising dif- fusion probabilistic models

Reference 19

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Observation 4467fa8f-e1d0-4cfc-8eb9-b720e18bd923 · outbound

This paper cites Video dif- fusion models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Video dif- fusion models

Reference 20

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Observation 63699cd7-05c4-4f73-b785-43fcb7be7244 · outbound

This paper cites LoRA: Low-rank adaptation of large language models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment LoRA: Low-rank adaptation of large language models

Reference 21

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Observation e47a2a94-5b3d-4d74-91c0-f467b6acf5ab · outbound

This paper cites Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation

Reference 22

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Observation 5b262491-79a5-4f11-ba1b-6e9472945dda · outbound

This paper cites Elucidating the design space of diffusion-based generative models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Elucidating the design space of diffusion-based generative models

Reference 23

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Observation 5a8188f3-3090-4a80-88c1-2d695987005c · outbound

This paper cites Repurpos- ing diffusion-based image generators for monocular depth estimation.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Repurpos- ing diffusion-based image generators for monocular depth estimation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:12.374917Z

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Observation c6df2a8a-af85-4e11-b4dc-c271c82d854d · outbound

This paper cites Understanding diffu- sion objectives as the elbo with simple data augmentation.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Understanding diffu- sion objectives as the elbo with simple data augmentation

Reference 25

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Observation 182072cb-a137-437d-b425-98584247c792 · outbound

This paper cites an unresolved cited work.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Unresolved cited work

Reference 26

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Observation 69fb86f0-a302-4e5e-b21d-1aabb7b03387 · outbound

This paper cites Improving the training of rectified flows.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Improving the training of rectified flows

Reference 27

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Observation 1133d6c4-0cbd-40e3-9519-60684f9a1341 · outbound

This paper cites Common diffusion noise schedules and sample steps are flawed.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Common diffusion noise schedules and sample steps are flawed

Reference 28

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Observation 0fd5534e-50c3-4f34-9280-8a73e6223725 · outbound

This paper cites Microsoft coco: Common objects in context.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Microsoft coco: Common objects in context

Reference 29

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Observation 93703b74-7ac5-495d-9005-3311b3a5f20f · outbound

This paper cites Flow Matching for Generative Modeling.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Flow Matching for Generative Modeling

Reference 30

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Observation 4c52cdeb-7932-49ff-b4ef-ac7ff4676e34 · outbound

This paper cites Au- dioldm: Text-to-audio generation with latent diffusion mod- els.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Au- dioldm: Text-to-audio generation with latent diffusion mod- els

Reference 31

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Observation a9288bda-7f85-4e5b-b272-501676b62165 · outbound

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

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 32

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Observation 42803282-daac-4045-a954-5a33b89917bd · outbound

This paper cites Instaflow: One step is enough for high-quality diffusion- based text-to-image generation.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Instaflow: One step is enough for high-quality diffusion- based text-to-image generation

Reference 33

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Observation f7a3e0c4-e90e-4652-9153-5ffbb70139f4 · outbound

This paper cites Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps

Reference 34

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Observation 31fa962c-2337-41e2-aac2-1fd287387479 · outbound

This paper cites Diffusion hyperfeatures: searching through time and space for semantic correspondence.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Diffusion hyperfeatures: searching through time and space for semantic correspondence

Reference 35

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Observation 5bc9a9ad-6133-478f-8300-e7f51e93a804 · outbound

This paper cites LCM-LoRA: A Universal Stable-Diffusion Acceleration Module.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment LCM-LoRA: A Universal Stable-Diffusion Acceleration Module

Reference 36

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Observation fd4c6d52-7a06-46d3-a29b-333bc1ac5793 · outbound

This paper cites SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers

Reference 37

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Observation 3054d0a8-5d02-4817-9ca8-474fe10b2f04 · outbound

This paper cites Fine-tuning image-conditional diffusion models is easier than you think.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Fine-tuning image-conditional diffusion models is easier than you think

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:10.327087Z

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Observation 52679af6-5c98-470a-9d41-1985177411e3 · outbound

This paper cites On distillation of guided diffusion models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment On distillation of guided diffusion models

Reference 39

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Observation 96d4537b-f846-417d-a521-aa3a9a2ab92b · outbound

This paper cites Indoor segmentation and support inference from rgbd images.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Indoor segmentation and support inference from rgbd images

Reference 40

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Observation 61e2bea4-75f7-41e0-9d24-1dcff0759871 · outbound

This paper cites Glide: Towards photorealis- tic image generation and editing with text-guided diffusion models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Glide: Towards photorealis- tic image generation and editing with text-guided diffusion models

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:09.946784Z

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Observation fb33c966-5050-48a6-b74e-4b48f4d2980a · outbound

This paper cites Scalable diffusion models with transformers.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Scalable diffusion models with transformers

Reference 42

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Observation 010479a1-0213-4a40-956c-5c9dc29de2ac · outbound

This paper cites Sdxl: Improving latent diffusion models for high-resolution image synthesis.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Sdxl: Improving latent diffusion models for high-resolution image synthesis

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:09.720622Z

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Observation 0b59607d-31c9-4f0d-9ad9-918f9dd02bc9 · outbound

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

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 44

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Observation f5365c08-cfd2-49ef-90d9-e1c90a50ba8c · outbound

This paper cites Susskind.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Susskind

Reference 45

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Source-reported events for the cited work

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Observation a22a4fbb-72a8-4617-abdd-543f4221ccad · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment High-resolution image synthesis with latent diffusion models

Reference 46

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Observation d245481c-2358-4167-87af-d99d4ad24d66 · outbound

This paper cites Low-rank adaptation for fast text- to-image diffusion fine-tuning.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Low-rank adaptation for fast text- to-image diffusion fine-tuning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:09.234129Z

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Observation dde4719c-5170-4d7b-a41c-f0c684e5051b · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Photorealistic text-to-image diffusion models with deep language understanding

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:09.027062Z

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Observation cead7f1f-7032-477e-b3c8-9ae3e366852b · outbound

This paper cites Progressive distillation for fast sampling of diffusion models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Progressive distillation for fast sampling of diffusion models

Reference 49

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Observation e51e8f78-9113-4390-9b9b-37b51c542c3a · outbound

This paper cites Adversarial diffusion distillation.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Adversarial diffusion distillation

Reference 50

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Observation f62b748c-a7e3-4957-b59b-14089bf70a18 · outbound

This paper cites Monocular Depth Estimation using Diffusion Models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Monocular Depth Estimation using Diffusion Models

Reference 51

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Source-reported events for the cited work

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Observation 3292057f-e716-4294-874b-a0e052c37ba0 · outbound

This paper cites A multi-view stereo benchmark with high- resolution images and multi-camera videos.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment A multi-view stereo benchmark with high- resolution images and multi-camera videos

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:08.798622Z

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Observation a5c544ad-6120-4e69-b739-1cd475547ba1 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:08.529539Z

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Observation 2d1c8ad0-5bb5-4bf6-bfa0-dab3aaee1a71 · outbound

This paper cites Boosting latent diffusion with flow match- ing.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Boosting latent diffusion with flow match- ing

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:08.340180Z

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Observation d9779b2e-53c0-4f18-8bd2-14a708ad5230 · outbound

This paper cites Bespoke Solvers for Generative Flow Models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Bespoke Solvers for Generative Flow Models

Reference 55

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Observation c3332ee6-5cb1-4f4a-a2ae-5ac67bb8d792 · outbound

This paper cites Denois- ing diffusion implicit models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Denois- ing diffusion implicit models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T11:34:04.521602Z

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Observation 2a658d97-a691-42cb-9d4d-6987d014a980 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Score-Based Generative Modeling through Stochastic Differential Equations

Reference 57

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Observation 73550a7a-9b08-4887-9ac7-bf600b94e075 · outbound

This paper cites Consistency models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Consistency models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:08.099595Z

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Observation cdedb216-4f22-4e79-9202-ef095ca9fd34 · outbound

This paper cites CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models

Reference 59

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Observation ad02aebd-de39-40dc-9a9d-33b3408882a3 · outbound

This paper cites Emergent correspondence from im- age diffusion.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Emergent correspondence from im- age diffusion

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:07.842580Z

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Observation 4642e35f-dad1-4c71-918e-c92347fa758c · outbound

This paper cites Improving and generalizing flow-based gen- erative models with minibatch optimal transport.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Improving and generalizing flow-based gen- erative models with minibatch optimal transport

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:07.620005Z

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Observation 14ac07bd-4129-4399-aa56-68c8f75bc536 · outbound

This paper cites Dai, Andrea F.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Dai, Andrea F

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:07.365097Z

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Observation 6d58f621-00be-4cbb-847b-87f84cacab1c · outbound

This paper cites Open-vocabulary panop- tic segmentation with text-to-image diffusion models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Open-vocabulary panop- tic segmentation with text-to-image diffusion models

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:07.126883Z

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Observation 09d023ca-7e5a-4dc7-9541-028ff014344b · outbound

This paper cites Perflow: Piecewise rectified flow as universal plug-and-play accelerator, 2024.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Perflow: Piecewise rectified flow as universal plug-and-play accelerator, 2024

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:06.921645Z

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Observation da54b21e-18f7-4472-ac26-439596bd0d4b · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Depth anything: Unleashing the power of large-scale unlabeled data

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:06.717559Z

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Observation 74412f08-06d0-4ffd-a2a3-b61b6aca16ac · outbound

This paper cites Depth Anything V2.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment Depth Anything V2

Reference 66

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Observation 87d761b5-1a3d-47cf-8cc1-f9181fbca22e · outbound

This paper cites IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T11:34:05.953733Z

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Observation 0a61bb08-d273-4344-87e2-5971c583c968 · outbound

This paper cites LoRA base.

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment LoRA base

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:06.486250Z

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Pith citing papers

Observation f0180740-5d93-476b-8863-53d1152ef251 · inbound

Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling cites this paper.

Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment

Reference 69

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Observation dd3f2424-bdf2-40b5-b989-5e8586110d37 · inbound

Cross-Space Distillation: Teaching One-Step Students with Modern Diffusion Teachers cites this paper.

Cross-Space Distillation: Teaching One-Step Students with Modern Diffusion Teachers Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment

Reference 43

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