Pith. sign in

Paper Citation Record · LEDGER

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

As of 10 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2507.22604.

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

pith.paper-citation-record.v1
2507.22604 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:32:43.042017Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

59 of 59 outbound references displayed

  • verified exact0
  • verified fuzzy34
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:39.827546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:39.827546Z digest=sha256:4adad891627a8f73d68fd881c759c817e8213068988f5b80c3f4a19da7b67138

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:32:43.684332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:39.888216Z digest=sha256:590f4b358eaa209ee3f61267ac026292bcdc8ad057dcd9af1b3bb760be5faf81

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:39.978762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:39.978762Z digest=sha256:74a834bb5572c2cae78aef0cbfff0d93876ca7270df98b9d454b8d2833955688

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:32:43.675040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:40.040511Z digest=sha256:fd7606f07d8175d8dd14d5f72d1ba46575dbb0a6d059d7d6962357a34b56c300

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:32:43.665536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:40.099892Z digest=sha256:f582d3746fdea698ad7ca54092cba79c9fe8a3d552e508fac9da8680af921b02

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:32:43.656224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:40.177039Z digest=sha256:ee242a8218d29880f83216d1be18f98ecedee41065f206d9b777a63fd1a948d4

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:40.241667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:40.241667Z digest=sha256:31346da3b1ac5b58e46f6a4109963140278e103990eb3b86d0c255f3e532e01b

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:32:43.645466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:40.330966Z digest=sha256:cf54e6e243067c1962240d0f5a55462cdddec84536aeb085307ac8e6152df8ca

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:32:43.634780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:40.389148Z digest=sha256:69e1165da36045c21709523483df5de180832c5bfcc92a708aa06b8b8ed18c22

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:40.501794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:40.501794Z digest=sha256:5072e74f3ceccaf3b9059eab4f4f6b07b27e58a9b38d4d4cd8505b5b4116eeb6

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:40.594896Z digest=sha256:11b9c364d512206e2d7fb9f1f03641d9d720ca40324ad6aba97053686f2408fa

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:40.687256Z digest=sha256:b0bc477846632b88abf569f887f9b7c2fc44d63d15c94c3eae85451286f9d8ee

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:40.803760Z digest=sha256:4a1ec6965c827cceb3471281a20125f41555c466ac6745758b972c1d096e7ad7

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:40.902608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:40.902608Z digest=sha256:61035b9b65695a32e00953a5ad4cd158562b87d79927f81a32cb52106cb65c4a

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:40.982714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:40.982714Z digest=sha256:a936610d56e9100c3fc423e19795d2d07a4d2577649644b95d63deabc5d268cc

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:41.041431Z digest=sha256:6c519359872ab47b025023e1c23b2fcd26ef8a1b5c81ecbde0642f455ea25583

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:41.088672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:41.088672Z digest=sha256:5fb69d52b85567c6a06266252991fff6b7e93b0c0c6248edb0b7d2cdc2417dc4

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:41.179323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:41.179323Z digest=sha256:e42b0c677058a1e19360f64d932d8af23ed14a8fe6de36b33a69e4beb9c85b1b

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:32:43.577274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:41.257372Z digest=sha256:c92676777f6eba75e19c3592351f32b7a6903f20589d9234ee340d7de9bcf7eb

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:41.327159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:41.327159Z digest=sha256:9ce01e800bd26b7d275eb07cd60e1166efc4b2f260e5ab37f361dbf0006d2ab8

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:41.352657Z digest=sha256:0704d7da6ae578295895e73510dc8c5423efce76f7d2452926d44c07ea375672

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:41.441247Z digest=sha256:14814c2bb7d09767d9ef5d3d2f290be152555dd9f0cb95762ba2f92860803211

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:41.521115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:41.521115Z digest=sha256:4eefb8b67a5950c0291d58fa101c79443937572c27e47ac731ae20de0ea46480

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:41.590785Z digest=sha256:b173b0b90f2d6036d2ac8d5609069dbe52a47774a7b55f0340e3c455617f8bd2

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:41.627848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:41.627848Z digest=sha256:a08606adf943384f8914b6e81e9d312fb1deedb42cc7b1f40550220d6715fcf9

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:41.740717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:41.740717Z digest=sha256:36745f36d1b1341728e901f41e8c4d78baa5674c2933a38c54629bfe39c1a9c6

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:41.788635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:41.788635Z digest=sha256:6062e1ca77c22f62414982339df34381fb10985cc205c2d4493ecaf0c05b899d

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:41.810872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:41.810872Z digest=sha256:56e4c757518804f9585420d5381124fb51560857dcd243392d6bdda954315f9a

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:41.872860Z digest=sha256:c22aeec62d5a7358d604cb799da6e11366565da1f4d53043ac7a38d2f19e3025

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:41.949449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:41.949449Z digest=sha256:e9473f9268a58ee620de5ad57e8edb048ed5660891e4fcd34ede8b94f0cf8a2d

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:42.033338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:42.033338Z digest=sha256:aaaa138fde58a438eee98d5bca7a9755a96021dd71a2607411daac53edb2c0bd

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:42.127897Z digest=sha256:8ed1df68e733474231df9eec94bdfd88935be81cc2bec318f2d0d13faf771a2f

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:42.196458Z digest=sha256:df12de9ce5b7c80bfe56ef846243050e9bf1ac44938ab9b1d8c61c4f73042ef7

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:42.332939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:42.332939Z digest=sha256:d6bc1e7b8aa9933cc2302f63a5ce511773f2e7d1a5d5524c653f489cc8791585

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:42.405313Z digest=sha256:27092a2064fd3ab5ea762f9edaed01aaf4ebedee872ae4af44d8a4f93926f9fd

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:42.517743Z digest=sha256:15a0f528284ec5177a2cc07309c6a5edc2ad0977d1bc1c67ebbafcb273d3c9b6

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:42.637511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:42.637511Z digest=sha256:8ca1f76fb5f803be0e87fcb0201dc52fd7ac36b6a53b0a4fa429093e383d1f0d

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:42.738454Z digest=sha256:f7601cd68443dfe71908e289c43351de45461bf982809cfb935b18f07d5800af

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:42.789265Z digest=sha256:a095784c3fdac3f1413dbe26e38e274dbf9a368cd3035f1884425976207fdb85

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:42.881489Z digest=sha256:e007977d19c80bfaeee198d8565718eccc493e907b32fa9b63204eb37ffa49a8

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:42.949430Z digest=sha256:b2771530e1e2711de1837c9a2fd3e8e4331fd0c428ea603e8b378d7a2e75a3d9

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:42.990133Z digest=sha256:e0bddb2e61ccf86a609b9af3fb2baf61a4798f9f4c318c4aa2e1efc4020de6f6

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:42.993236Z digest=sha256:28356d75e5a36dc0213b2a3b4b2708870048800d948c7e96267cdde34c2a34f7

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:42.996734Z digest=sha256:454dd366feb3dbe2530d5351cd26b4c44c4a5e37b8573c5f9158892a9beacc08

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:43.000019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:43.000019Z digest=sha256:695c5c674fb74c56b670a3cc976098cc3fa803d7e951e54ea6d203138ecaf2ab

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T11:32:43.431396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:43.003738Z digest=sha256:5a0779e15e84e74b35c2a37ea8ce955a0acdbf8735edf6bbda046a7d0bec8aa6

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:43.006780Z digest=sha256:8c8779583e9fe9d85efaf44afe63beda90300f0a09adca83859558833541c6e4

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:43.009674Z digest=sha256:c00ea2017872a926f3f4bb7d399678ae484a899ab111b70775a8e431aa9104f0

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:43.012513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:43.012513Z digest=sha256:959ba98f33923dd98a7388d670039e4821e69644ba2cbc93a2696c1e1139a2f5

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:43.016250Z digest=sha256:b51c3c64d79966377b6e870d40e19866d8b75f9bddbe474ba40f08cca6696abf

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:43.019078Z digest=sha256:876f8729ed121777a2e152cf876e08388049e1490a60955c337b3af178d452e1

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:43.021975Z digest=sha256:0f0786dae91ec0aa9cc0d809497ef9efeb53831f1b2a0cc3115933dc3071cbcf

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:43.024781Z digest=sha256:69f10a8d10465af20e66f58e4a2fb63ade4345e0b621d5f8addb40728e669534

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:43.027721Z digest=sha256:00c835a789c7029e1d69cd8ada3dc68e263fabd2f5aaf2b661fba16d48218be1

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

Resolution
unresolved
no resolver link, observed 2026-08-06T11:32:43.030529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:43.030529Z digest=sha256:75d2d78e59f56b37f3975ff144398de2e6a383bddaf046c534600c7280fb7dd7

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:43.033600Z digest=sha256:a2e1dc71c8c65e89bda579051e03d28921d1384f09f175846b5e6af690e3dca1

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:43.036357Z digest=sha256:3db330d6a43ee2ae8efaf233145b30b42633caae47541f972974d73bb7922424

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T11:32:43.039168Z digest=sha256:ccfe561489326c0250bdde289b57e29a24d6e303fab16446b0a7b17dabfd1f49

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:32:43.042017Z digest=sha256:d619ed1bf3b5edf05421a7c16f9bf6a61fea01afb18c8f15a9a43634ccf6164a

Pith citing papers

No inbound Pith citation observations are available.