ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning | Paper Citation Record

Observation 25cbc780-269d-4c77-afc9-00fb10c257ad · outbound

This paper cites eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers

Reference 1

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Observation c2f1f8cc-5364-402c-bbb0-9c4c6a5d2b24 · outbound

This paper cites Improving image generation with better captions.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Improving image generation with better captions

Reference 2

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Observation a7b42432-0e2a-403d-81f6-691c4e6a21d5 · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Training Diffusion Models with Reinforcement Learning

Reference 3

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Observation b6b8613f-8cd8-43e9-8f36-421b4ca3bdd0 · outbound

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

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Enhancing diffusion models with text-encoder reinforcement learning

Reference 4

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Observation 0346f274-1f9a-494c-b17a-f123c494d230 · outbound

This paper cites Deep reinforcement learn- ing from human preferences.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Deep reinforcement learn- ing from human preferences

Reference 5

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Observation 4da82a2e-73c1-4b52-ac06-c186fda0b48f · outbound

This paper cites Directly fine-tuning diffusion models on differentiable re- wards.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Directly fine-tuning diffusion models on differentiable re- wards

Reference 6

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Observation 865f7677-941a-479e-b69a-653f3781c75c · outbound

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

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

Reference 7

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Observation eeb93c00-a8f2-492e-b227-2706a4f3703b · outbound

This paper cites Prdp: Proximal reward difference prediction for large-scale reward finetuning of diffusion models.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Prdp: Proximal reward difference prediction for large-scale reward finetuning of diffusion models

Reference 8

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Observation 2c1d864f-f7ab-4155-815e-8529e323f8b4 · outbound

This paper cites Diffusion models beat gans on image synthesis.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Diffusion models beat gans on image synthesis

Reference 9

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Observation 78b6908b-4571-452b-80b3-3388bf9ae5bd · outbound

This paper cites RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment

Reference 10

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Observation 2d66365f-b9d6-4385-b70f-0ad6229c4890 · outbound

This paper cites Re- inforcement learning for fine-tuning text-to-image diffusion models.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Re- inforcement learning for fine-tuning text-to-image diffusion models

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.624389Z

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Observation e102b90d-e08a-4aaa-b9ed-15d73472921f · outbound

This paper cites Re- inforcement learning for fine-tuning text-to-image diffusion models.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Re- inforcement learning for fine-tuning text-to-image diffusion models

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.614539Z

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Observation 523a8d4c-b929-4bd4-850a-a07c41c1c59f · outbound

This paper cites Policy shaping: Integrating human feedback with reinforcement learning.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Policy shaping: Integrating human feedback with reinforcement learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.604067Z

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Observation 43c608fd-0697-46a1-9f25-16bf587391e6 · outbound

This paper cites Matryoshka Diffusion Models.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Matryoshka Diffusion Models

Reference 14

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Observation 90028241-a900-423e-a271-7885a9fa2f49 · outbound

This paper cites I4VGen: Image as Free Stepping Stone for Text-to-Video Generation.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning I4VGen: Image as Free Stepping Stone for Text-to-Video Generation

Reference 15

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Observation 44242b4b-a453-45ce-802d-faf065fa2e6a · outbound

This paper cites Initno: Boosting text-to-image diffu- sion models via initial noise optimization.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Initno: Boosting text-to-image diffu- sion models via initial noise optimization

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.593412Z

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Observation 2031fbf8-579e-4113-971d-96fa408288ef · outbound

This paper cites Classifier-Free Diffusion Guidance.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Classifier-Free Diffusion Guidance

Reference 17

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Observation 229f86d2-3386-43f1-ba52-3e4781710952 · outbound

This paper cites Denoising diffu- sion probabilistic models.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Denoising diffu- sion probabilistic models

Reference 18

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Observation 8616d157-f3ff-463d-824c-6f918f845753 · outbound

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

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Lora: Low-rank adaptation of large language models

Reference 19

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Observation 8ee13c69-5fd7-4a62-96ac-6e48a7cf4f9a · outbound

This paper cites T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation

Reference 20

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Observation e37d7e36-0909-4601-853a-472054a9f789 · outbound

This paper cites Distilling diffusion models into condi- tional gans.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Distilling diffusion models into condi- tional gans

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.562327Z

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Observation 261aef29-6342-49d6-b8ad-595e8c094310 · outbound

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

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Elucidating the design space of diffusion-based generative models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.553697Z

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Observation 8b6e5a40-a53f-4e7c-a407-9f5ca1dc9b53 · outbound

This paper cites Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion

Reference 23

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Observation 919ceb88-56c5-429e-8fc7-599b142fd77e · outbound

This paper cites Pick-a-pic: An open dataset of user preferences for text-to-image generation.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Pick-a-pic: An open dataset of user preferences for text-to-image generation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.544701Z

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Observation e7ff8769-1b27-43a3-bfed-01b5d71ea8e5 · outbound

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

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Aligning Text-to-Image Models using Human Feedback

Reference 25

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Observation 17a06130-4c41-4fea-9309-83de37721bb3 · outbound

This paper cites Reward Guided Latent Consistency Distillation.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Reward Guided Latent Consistency Distillation

Reference 26

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Observation 07ef3d34-9444-4738-a6f1-6d3f3f07fe95 · outbound

This paper cites T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback

Reference 27

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Observation b179a1dd-45bd-406b-9afb-39a360bfd541 · outbound

This paper cites T2v- turbo-v2: Enhancing video generation model post-training through data, reward, and conditional guidance design.arXiv preprint arXiv:2410.05677, 2024.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning T2v- turbo-v2: Enhancing video generation model post-training through data, reward, and conditional guidance design.arXiv preprint arXiv:2410.05677, 2024

Reference 28

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Observation bb68dcf6-65f8-4452-85de-9aa11daedf9c · outbound

This paper cites Aligning diffusion mod- els by optimizing human utility.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Aligning diffusion mod- els by optimizing human utility

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.534686Z

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Observation f277eed4-bd71-49b1-b5b2-b9c8abba75c7 · outbound

This paper cites Aesthetic Post-Training Diffusion Models from Generic Preferences with Step-by-step Preference Optimization.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Aesthetic Post-Training Diffusion Models from Generic Preferences with Step-by-step Preference Optimization

Reference 30

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Observation eb2563d1-687b-40c0-94e0-702bff7999db · outbound

This paper cites SDXL-Lightning: Progressive Adversarial Diffusion Distillation.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning SDXL-Lightning: Progressive Adversarial Diffusion Distillation

Reference 31

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Observation 5ff8a7eb-d65c-456f-ab9c-1b1936dcf79a · outbound

This paper cites Improved denoising diffusion probabilistic models.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Improved denoising diffusion probabilistic models

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.525362Z

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Observation c516e9ef-c8bd-4b1f-aa5c-59913d658c38 · outbound

This paper cites Training lan- guage models to follow instructions with human feedback.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Training lan- guage models to follow instructions with human feedback

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.515629Z

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Observation 7e5c2d48-2831-46f9-941b-078d87e9a147 · outbound

This paper cites Aligning Text-to-Image Diffusion Models with Reward Backpropagation.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Aligning Text-to-Image Diffusion Models with Reward Backpropagation

Reference 34

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Observation 233eac4c-7592-4fc9-bba0-16c5b1df4f88 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Learn- ing transferable visual models from natural language super- vision

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.505533Z

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Observation df07502c-7e7a-46db-b902-a4993d098ec9 · outbound

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

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Direct preference optimization: Your language model is secretly a reward model

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.495587Z

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Observation 43271464-f816-413c-8fa3-08e3100a3f34 · outbound

This paper cites Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 37

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Observation c99a38ce-873f-4eef-a5e1-5db250ce477f · outbound

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

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning High-resolution image syn- thesis with latent diffusion models

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.484757Z

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Observation 1fde45e0-7978-44bc-8dca-02e92463b17c · outbound

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

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Progressive distillation for fast sampling of diffusion models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.474767Z

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Observation c2630b46-6348-4a3a-8ff0-c975fe614cf0 · outbound

This paper cites Fast High-Resolution Image Synthesis with Latent Adversarial Diffusion Distillation.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Fast High-Resolution Image Synthesis with Latent Adversarial Diffusion Distillation

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T11:32:42.881489Z

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Observation 30693c5b-509d-4a56-bd04-70cb140f0f94 · outbound

This paper cites Adversarial diffusion distillation.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Adversarial diffusion distillation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.465530Z

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Observation 523df69a-7ad3-4927-ab52-2f6eedcac486 · outbound

This paper cites Laoin aes- thetic predictor.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Laoin aes- thetic predictor

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.456014Z

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Observation dbd550c2-0619-40a5-9825-138f9947fe8f · outbound

This paper cites A Picture is Worth a Thousand Words: Principled Recaptioning Improves Image Generation.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning A Picture is Worth a Thousand Words: Principled Recaptioning Improves Image Generation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T11:32:42.993236Z

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Observation 5c429a3e-0217-44b1-a135-6be6acdf606c · outbound

This paper cites Denois- ing diffusion implicit models.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Denois- ing diffusion implicit models

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.446844Z

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Observation cc57130b-9c09-49ec-ba91-9223f726e7cc · outbound

This paper cites Score-based generative modeling through stochastic differential equa- tions.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Score-based generative modeling through stochastic differential equa- tions

Reference 45

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Observation 87b22598-2518-45d8-b13c-f9a42126bc2e · outbound

This paper cites Consistency models.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Consistency models

Reference 46

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Observation b8f2c748-b4c8-4f32-9d7f-d25c46aa1e75 · outbound

This paper cites Learning to summarize with human feed- back.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Learning to summarize with human feed- back

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.421960Z

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Observation 51c4f1c2-4711-4a17-bd8d-f4b43c001f97 · outbound

This paper cites Diffusion model align- ment using direct preference optimization.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Diffusion model align- ment using direct preference optimization

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.412138Z

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Observation 99bbd271-ba81-4177-984c-13ecf11a9bb1 · outbound

This paper cites Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 49

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Observation 8c1114ed-24b9-4407-becf-1cfbc77fcc10 · outbound

This paper cites Human preference score: Better aligning text-to- image models with human preference.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Human preference score: Better aligning text-to- image models with human preference

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.402812Z

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Observation e06b552b-3a31-4dc9-bbea-48d295720320 · outbound

This paper cites Deep reward supervisions for tuning text-to-image diffusion models.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Deep reward supervisions for tuning text-to-image diffusion models

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.393293Z

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Observation ea72b0f4-9254-4442-bdba-df43ddb69120 · outbound

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

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Imagere- ward: Learning and evaluating human preferences for text- to-image generation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.383376Z

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Observation 45cc5dd3-f16e-4f4c-b041-08de355b4aec · outbound

This paper cites Raphael: Text-to-image generation via large mixture of diffusion paths.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Raphael: Text-to-image generation via large mixture of diffusion paths

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.374273Z

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Observation ba402e0d-a5ac-4a1b-8671-46f19cb3604d · outbound

This paper cites Using human feedback to fine-tune diffusion models without any reward model.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Using human feedback to fine-tune diffusion models without any reward model

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.365306Z

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Observation 63e922f5-96b5-46a3-a6ff-24466acb8031 · outbound

This paper cites A Dense Reward View on Aligning Text-to-Image Diffusion with Preference.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning A Dense Reward View on Aligning Text-to-Image Diffusion with Preference

Reference 55

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Observation e93f01fd-97cc-46ab-94e8-948efde05d08 · outbound

This paper cites One-step diffusion with distribution matching distillation.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning One-step diffusion with distribution matching distillation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.355625Z

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Observation 504a4065-4aec-41fa-acca-877216104575 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Adding conditional control to text-to-image diffusion models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-06T11:32:43.036357Z

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Observation e7b8362d-407e-4037-af34-0cedc226ff6f · outbound

This paper cites Large-scale reinforcement learning for diffusion models.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Large-scale reinforcement learning for diffusion models

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:32:43.339279Z

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Observation e9373621-7776-4932-a4b3-af79a8b72577 · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Fine-Tuning Language Models from Human Preferences

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T11:32:43.042017Z

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