Paper Citation Record · LEDGER

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization

As of 19 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2505.20975.

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

pith.paper-citation-record.v1
2505.20975 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:50:03.326257Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eb256cc1-8e04-4a68-9fed-b83fac120b93 · outbound

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

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T13:49:58.881550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dce72ee-5fb4-4748-ac46-41c630dbe6b0 · outbound

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

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Photorealistic text-to-image diffusion models with deep language understanding,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:10.841388Z

Source-reported events for the cited work

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Observation 7b0ee646-87d5-44a6-9a2b-0aa77edec3b9 · outbound

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

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization High-resolution image synthesis with latent diffusion models,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T13:49:59.098373Z

Source-reported events for the cited work

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Observation 14897731-80bb-43ac-b432-b1616b9ea7f2 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:10.575399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 389028f6-7a34-4ab4-9f35-b82564ddf24b · outbound

This paper cites An image is worth one word: Personalizing text-to-image generation using textual inversion,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization An image is worth one word: Personalizing text-to-image generation using textual inversion,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:10.344119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 39c5280c-19fc-4c8f-a351-7dbb3394c3e0 · outbound

This paper cites Id-aligner: Enhancing identity- preserving text-to-image generation with reward feedback learning,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Id-aligner: Enhancing identity- preserving text-to-image generation with reward feedback learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:10.184311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 472f1d7a-5c0b-4db0-ad71-4ccd6a72ac73 · outbound

This paper cites Proximal preference optimization for diffusion models,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Proximal preference optimization for diffusion models,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:09.977946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 880df1b6-ebca-4fd1-976c-22feece3d93d · outbound

This paper cites Versat2i: Improving text-to-image models with versatile reward,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Versat2i: Improving text-to-image models with versatile reward,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:09.819079Z

Source-reported events for the cited work

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Observation 1e634ca9-de88-4210-be35-9a7b6bb85f74 · outbound

This paper cites Imagereward: Learning and evaluating human preferences for text-to-image generation,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Imagereward: Learning and evaluating human preferences for text-to-image generation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:09.632234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8a77b5d1-75cf-4d22-8770-4ec05998c8bf · outbound

This paper cites Elucidating optimal reward-diversity tradeoffs in text-to-image diffusion models,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Elucidating optimal reward-diversity tradeoffs in text-to-image diffusion models,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:09.414794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 222836f8-4a79-4c69-aef5-ca4ccefa34d4 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Direct preference optimization: Your language model is secretly a reward model,

Reference 11

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Source-reported events for the cited work

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Observation df87d232-5a89-487e-ac82-e6f24f725d75 · outbound

This paper cites Svdiff: Compact parameter space for diffusion fine-tuning,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Svdiff: Compact parameter space for diffusion fine-tuning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:09.241389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3d6b4452-6d5a-4c37-b998-991325db4b5b · outbound

This paper cites Multi-concept customization of text-to-image diffusion,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Multi-concept customization of text-to-image diffusion,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:09.049956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cfef7280-f73b-4106-85f6-93e22fe74bb3 · outbound

This paper cites Idadapter: Learning mixed features for tuning-free personalization of text-to-image models,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Idadapter: Learning mixed features for tuning-free personalization of text-to-image models,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:08.874938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cf50bf33-2535-401d-b5a9-7d2973804dae · outbound

This paper cites Elite: Encoding visual concepts into textual embeddings for customized text-to-image generation,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Elite: Encoding visual concepts into textual embeddings for customized text-to-image generation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:08.578301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 93a898bc-4ddf-4047-8e95-48b54b40839a · outbound

This paper cites Hyperdreambooth: Hypernetworks for fast personalization of text-to-image models,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Hyperdreambooth: Hypernetworks for fast personalization of text-to-image models,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:08.265001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dcd9344f-e251-4125-8c00-339d0145f7a9 · outbound

This paper cites Blip-diffusion: Pre-trained subject representation for controllable text-to-image generation and editing,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Blip-diffusion: Pre-trained subject representation for controllable text-to-image generation and editing,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:07.944540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4bbfeafb-d449-4e1a-aa8a-17142dd34de4 · outbound

This paper cites Subject-diffusion:open domain personalized text-to-image generation without test-time fine-tuning,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Subject-diffusion:open domain personalized text-to-image generation without test-time fine-tuning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:07.684279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9434dca1-6378-4738-9323-31076e436920 · outbound

This paper cites Enhancing diffusion models with text-encoder reinforcement learning,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Enhancing diffusion models with text-encoder reinforcement learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:07.367850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 310ec11a-3b5a-4253-94e5-929a10616563 · outbound

This paper cites Towards better alignment: Training diffusion models with reinforcement learning against sparse rewards,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Towards better alignment: Training diffusion models with reinforcement learning against sparse rewards,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:07.092319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 00fc7862-dce2-4282-983e-59fb79e86688 · outbound

This paper cites Diffusion model alignment using direct preference optimization,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Diffusion model alignment using direct preference optimization,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:06.749823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4ad55f5e-0294-46e9-9cc9-a33b42547b38 · outbound

This paper cites Tuning timestep-distilled diffusion model using pairwise sample optimization,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Tuning timestep-distilled diffusion model using pairwise sample optimization,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:06.346983Z

Source-reported events for the cited work

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Observation 00b7e375-6fe9-4fb0-8182-8340284dadf4 · outbound

This paper cites Patchdpo: Patch-level dpo for finetuning-free personalized image generation,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Patchdpo: Patch-level dpo for finetuning-free personalized image generation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:05.980663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e96ac835-2e05-408a-8909-8ebbd0feb3a8 · outbound

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

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization High-resolution image synthesis with latent diffusion models,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:05.689612Z

Source-reported events for the cited work

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Observation 263e868b-cf4b-44e5-b4c5-c8243145012f · outbound

This paper cites Auto-encoding variational bayes,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Auto-encoding variational bayes,

Reference 25

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Observation d75def03-a022-41f8-a71d-48be5cc0786b · outbound

This paper cites Denoising diffusion implicit models,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Denoising diffusion implicit models,

Reference 26

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Source-reported events for the cited work

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Observation 15324aed-3188-478a-8d29-9325a053613e · outbound

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

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Training language models to follow instructions with human feedback,

Reference 27

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Source-reported events for the cited work

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Observation c46f33e1-f6d0-4b01-92ee-1bc1748694a9 · outbound

This paper cites Realcustom: Narrowing real text word for real-time open-domain text-to-image customization,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Realcustom: Narrowing real text word for real-time open-domain text-to-image customization,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:05.156276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 09727e1c-d7a4-4c23-9fce-f8241ee9caa8 · outbound

This paper cites Beyond fine-tuning: A systematic study of sampling techniques in personalized image generation,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Beyond fine-tuning: A systematic study of sampling techniques in personalized image generation,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:04.898712Z

Source-reported events for the cited work

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Observation 1fff47ed-eead-496c-b4f6-c788c9463df7 · outbound

This paper cites Photoswap: Personalized subject swapping in images,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Photoswap: Personalized subject swapping in images,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:04.625710Z

Source-reported events for the cited work

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Observation d4993356-3d3f-4b1a-8513-01c46ebc92ec · outbound

This paper cites Enhancing detail preservation for customized text-to- image generation: A regularization-free approach,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Enhancing detail preservation for customized text-to- image generation: A regularization-free approach,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:04.449207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7ec7d4ff-9626-4e4f-b34f-00cf9e06c881 · outbound

This paper cites Microsoft coco: Common objects in context,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Microsoft coco: Common objects in context,

Reference 32

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Source-reported events for the cited work

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Observation 22446074-ae31-4533-8ef4-26b09ea458c1 · outbound

This paper cites Gpt-4 technical report,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Gpt-4 technical report,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:04.302817Z

Source-reported events for the cited work

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Observation ec364cf1-9f4d-4a9b-934e-0da259922cf1 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Learning transferable visual models from natural language supervision,

Reference 34

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Source-reported events for the cited work

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Observation 747bcdf2-e09c-46f8-a28b-8e4f1de0370b · outbound

This paper cites Pseudo numerical methods for diffusion models on manifolds,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Pseudo numerical methods for diffusion models on manifolds,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:04.130697Z

Source-reported events for the cited work

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Observation 78ef03d5-9229-4ff6-87a4-3f07122c2194 · outbound

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

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Elucidating the design space of diffusion-based generative models,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:03.939849Z

Source-reported events for the cited work

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Observation 1ce82a0e-61e8-40e3-8ebd-e1931db00ac7 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization U-net: Convolutional networks for biomedical image segmentation,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:02.856336Z

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Observation 2bba11cf-9c38-4cfd-955c-7443f1d33edb · outbound

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

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Sdxl: Improving latent diffusion models for high-resolution image synthesis,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:03.759112Z

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Observation 20978567-28a3-495b-b2b1-9a10329db199 · outbound

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

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Lora: Low-rank adaptation of large language models,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:03.685324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6a402cd2-b718-4c79-8add-1a64dd607db9 · outbound

This paper cites Which image is more consistent with the text prompt?.

DreamBoothDPO: Improving Personalized Generation using Direct Preference Optimization Which image is more consistent with the text prompt?

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:50:03.674299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

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