Paper Citation Record · LEDGER

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples

As of 8 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 4 inbound Pith citation observations for arXiv:2505.22002.

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

pith.paper-citation-record.v1
2505.22002 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:23:13.232281Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:32:13.061231Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T00:14:04.763204Z

Reference resolution

53 of 53 outbound references displayed

verified exact0
verified fuzzy1
unresolved51
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 555c8067-fad8-46a3-a03e-ee56fb3339ac · outbound

This paper cites a cat playing chess.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples a cat playing chess

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:15.369378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 65feb258-915e-4f25-925e-efff7574de75 · outbound

This paper cites an unresolved cited work.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:23:15.148362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 25782779-e3d9-4e4a-a606-4aa42e6df935 · outbound

This paper cites MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editing.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editing

Reference 4

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Observation 3a8cff3d-d226-4972-ad8c-cd17f12c0b71 · outbound

This paper cites Diffusion Policy: Visuomotor Policy Learning via Action Diffusion.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:01.681084Z

Source-reported events for the cited work

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Observation cab5368b-98e2-4836-adbe-30abf0c65cf7 · outbound

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

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Directly Fine-Tuning Diffusion Models on Differentiable Rewards

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:01.857245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ecb4595-6c47-4649-8996-0a1dfef93ef1 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:02.243017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfadfe4b-fe21-42a6-a158-e37ddc665651 · outbound

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

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:02.418961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb3fc34d-7ebe-4f2a-a66d-134fd9f89aa2 · outbound

This paper cites Prompt-to-Prompt Image Editing with Cross Attention Control.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Prompt-to-Prompt Image Editing with Cross Attention Control

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:02.599283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ff9c380-b6e0-4d01-9d5e-d3f75dc064f0 · outbound

This paper cites CLIPScore: A Reference-free Evaluation Metric for Image Captioning.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:02.807042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 055f8554-e976-4e3a-89e4-d991cee6599f · outbound

This paper cites Classifier-Free Diffusion Guidance.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Classifier-Free Diffusion Guidance

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:02.952670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9ec8f4e-18d2-40a3-ba0c-ce9d6d23c0b7 · outbound

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

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples LoRA: Low-Rank Adaptation of Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:03.292947Z

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Observation a414adea-0be0-4f8e-8f7a-dc34d30893c4 · outbound

This paper cites doi: 10.1145/3703155.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples doi: 10.1145/3703155

Reference 16

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Source-reported events for the cited work

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Observation e7ae4da1-4a0c-4d71-853f-c81917c6b9bb · outbound

This paper cites CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:03.828401Z

Source-reported events for the cited work

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Observation 8254a454-61fc-4f23-810f-42734a3871a0 · outbound

This paper cites Imagic: Text-Based Real Image Editing with Diffusion Models.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Imagic: Text-Based Real Image Editing with Diffusion Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:03.995514Z

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Observation 1c346a8e-77b2-476e-a1e4-e65f339be3a7 · outbound

This paper cites SDPO: Segment-Level Direct Preference Optimization for Social Agents.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples SDPO: Segment-Level Direct Preference Optimization for Social Agents

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:04.117228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e1734a6-acea-491d-8039-6c7dd6a19905 · outbound

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

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Aligning Text-to-Image Models using Human Feedback

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:04.252641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b462b511-c8d5-45d8-b1b3-5ee1f1631a3a · outbound

This paper cites Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:04.358322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75c08bd0-bfac-4552-af51-3094f9366dc1 · outbound

This paper cites Null-text Inversion for Editing Real Images using Guided Diffusion Models.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Null-text Inversion for Editing Real Images using Guided Diffusion Models

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4233c6f0-a7fb-49ef-8a49-d276128fed8e · outbound

This paper cites Fast Prompt Alignment for Text-to-Image Generation.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Fast Prompt Alignment for Text-to-Image Generation

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b20144f8-927e-42f5-9f2a-04f10f3efd2a · outbound

This paper cites Training language models to follow instructions with human feedback.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Training language models to follow instructions with human feedback

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8f4a08b-dbe4-4c3b-bc45-18239e48d035 · outbound

This paper cites Scalable Diffusion Models with Transformers.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Scalable Diffusion Models with Transformers

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e10309dc-8029-45d0-88bd-1aefc24c8ca9 · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples DreamFusion: Text-to-3D using 2D Diffusion

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:07.456286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbb02988-905c-4a91-a752-c27ffe2b99b0 · outbound

This paper cites Diffusion Autoencoders: Toward a Meaningful and Decodable Representation.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Diffusion Autoencoders: Toward a Meaningful and Decodable Representation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:07.623938Z

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Unavailable: canonical work link unavailable.

Observation 8bb66da3-0afc-4d37-824e-6ae84e45fd9d · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Learning Transferable Visual Models From Natural Language Supervision

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:08.111582Z

Source-reported events for the cited work

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Observation 720f7d71-1a73-46b3-a8a9-4c93d02750ad · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:09.937975Z

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Observation 095c8792-5f6a-4fc5-ad5f-b4aefe4509f1 · outbound

This paper cites High-Resolution Image Synthesis with Latent Diffusion Models.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples High-Resolution Image Synthesis with Latent Diffusion Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:10.048591Z

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Observation 9f173aeb-507a-483f-937d-b3c8f7d7073f · outbound

This paper cites DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing

Reference 34

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Observation d0401a6a-68df-461d-8c5e-40b135bef54c · outbound

This paper cites Deep Unsupervised Learning using Nonequilibrium Thermodynamics.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Reference 35

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Observation cb9426ff-2214-4f9a-8080-116c14c56d80 · outbound

This paper cites Denoising Diffusion Implicit Models.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Denoising Diffusion Implicit Models

Reference 36

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Observation 797b8c62-23d6-4688-8e36-80a60f2f74d9 · outbound

This paper cites Improved Techniques for Training Score-Based Generative Models.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Improved Techniques for Training Score-Based Generative Models

Reference 37

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Observation e6f651d2-0b8c-43b9-b898-1407a1a25645 · outbound

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D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Unresolved cited work

Reference 38

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Observation 1567cb64-eba7-4cfd-a546-41f62aa51bc2 · outbound

This paper cites How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 39

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Observation a340ab0d-fd6b-4896-8517-6484cb316afc · outbound

This paper cites Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:11.429291Z

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Observation ae06d4f7-f05e-4e6c-a785-ccc839ac2678 · outbound

This paper cites Attention Is All You Need.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Attention Is All You Need

Reference 41

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Observation ebb1aaea-ca66-4040-b019-22d9a329bd5b · outbound

This paper cites Diffusion Model Alignment Using Direct Preference Optimization.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Diffusion Model Alignment Using Direct Preference Optimization

Reference 42

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Observation 422a07d5-0ade-481a-93e5-3e6f3d5c923b · outbound

This paper cites Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpainting.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpainting

Reference 43

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Observation a3456976-8d19-41d6-8adf-41f159710c7c · outbound

This paper cites AttnGCG: Enhancing Jailbreaking Attacks on LLMs with Attention Manipulation.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples AttnGCG: Enhancing Jailbreaking Attacks on LLMs with Attention Manipulation

Reference 44

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Observation 098b5ba6-712a-4421-b688-ae65ff339045 · outbound

This paper cites Fine-Grained Human Feedback Gives Better Rewards for Language Model Training.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Fine-Grained Human Feedback Gives Better Rewards for Language Model Training

Reference 45

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Observation 3060bb09-27e8-46ce-9a32-a562f8df7118 · outbound

This paper cites ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation

Reference 46

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Observation 7e8e2fb8-3024-4f03-9424-203a8b96e992 · outbound

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

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation

Reference 47

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Observation c479fbc2-c7c6-46ba-9dd9-7a2e670d54f1 · outbound

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D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model

Reference 48

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Observation d30fad13-688f-472a-8fa6-10ece99ac71b · outbound

This paper cites Align, Adapt and Inject: Sound-guided Unified Image Generation.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Align, Adapt and Inject: Sound-guided Unified Image Generation

Reference 49

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Observation ec1ab486-8a66-4f9a-95ce-5a0ed0c2bd63 · outbound

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D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback

Reference 50

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Observation c60dde6b-f476-4227-9157-f03b5e4afb38 · outbound

This paper cites LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation

Reference 51

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D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 2015

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Observation 9f8acd2c-8092-41aa-b313-5aca31293763 · outbound

This paper cites Visual Relationship Detection with Language Priors.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Visual Relationship Detection with Language Priors

Reference 2016

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Observation 479aa011-f2ea-48ec-9687-b7d731dee3bc · outbound

This paper cites Proximal Policy Optimization Algorithms.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Proximal Policy Optimization Algorithms

Reference 2017

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Observation eae8015b-9296-4197-9adc-90384ab2461f · outbound

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D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Denoising Diffusion Probabilistic Models

Reference 2020

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Observation 36f45c74-5c15-436e-bd58-a2168113b18a · outbound

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D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Diffusion Models Beat GANs on Image Synthesis

Reference 2021

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Observation 2f329f97-1758-46c0-bbff-d99d17cf7c00 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Constitutional AI: Harmlessness from AI Feedback

Reference 2022

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Observation fdc78d5b-3e9c-4473-89d0-cfb761724a05 · outbound

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D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples InstructPix2Pix: Learning to Follow Image Editing Instructions

Reference 2023

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D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Hallucination of Multimodal Large Language Models: A Survey

Reference 2024

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Observation 2c0a9f22-4a7e-4eab-b5c2-0342d3b9d6c4 · outbound

This paper cites Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse Rewards.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse Rewards

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T13:23:03.425660Z

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Pith citing papers

Observation 677826cb-de02-4929-9679-b1925de96318 · inbound

CAT: Causal Attention Tuning For Injecting Fine-grained Causal Knowledge into Large Language Models cites this paper.

CAT: Causal Attention Tuning For Injecting Fine-grained Causal Knowledge into Large Language Models D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T12:32:13.061231Z

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Observation b9fe8573-fd92-4b3f-8bb4-0b2a1dbdbda2 · inbound

HP-Edit: A Human-Preference Post-Training Framework for Image Editing cites this paper.

HP-Edit: A Human-Preference Post-Training Framework for Image Editing D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-10T03:29:21.991785Z

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Observation 23dd579a-9728-4b0b-b4c2-918929da3a5a · inbound

SpatialFusion: Endowing Unified Image Generation with Intrinsic 3D Geometric Awareness cites this paper.

SpatialFusion: Endowing Unified Image Generation with Intrinsic 3D Geometric Awareness D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:46:26.784659Z

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Observation ef9aca14-7908-42ed-aaf8-dbb5884d17c5 · inbound

Towards Anatomically Plausible Human Image Generation via Synthetic Localized Preferences cites this paper.

Towards Anatomically Plausible Human Image Generation via Synthetic Localized Preferences D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T00:14:04.764679Z

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