Paper Citation Record · LEDGER

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation

As of 21 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2511.20889.

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

pith.paper-citation-record.v1
2511.20889 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T20:11:28.708083Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

36 of 36 outbound references displayed

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verified fuzzy0
unresolved36
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e1be7f75-dd20-433d-853a-ae5beecda95f · outbound

This paper cites Training diffusion models with reinforce- ment learning.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Training diffusion models with reinforce- ment learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:24.342294Z

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Unavailable: canonical work link unavailable.

Observation 207c4a04-36af-441b-9c27-1e88f8e5e564 · outbound

This paper cites McCann, Marc Klasky, and Jong Chul Ye.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation McCann, Marc Klasky, and Jong Chul Ye

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:24.486940Z

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Observation a3e39e0b-fb9f-4c79-bbf8-af7dd31e671a · outbound

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

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Directly Fine-Tuning Diffusion Models on Differentiable Rewards

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:24.640413Z

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Observation d2cf6b0c-dfc4-4072-b8fc-2daabe89c3e8 · outbound

This paper cites Diffusion models beat gans on image synthesis.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Diffusion models beat gans on image synthesis

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:24.773760Z

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Observation 773446bd-a6d3-4d42-ab8d-19fe9c10e11f · outbound

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

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:24.902328Z

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Observation 32c04b56-3d93-4748-80c7-4e3cf231d8c9 · outbound

This paper cites Diffusion posterior sampling for linear inverse problem solving: A filtering perspective.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Diffusion posterior sampling for linear inverse problem solving: A filtering perspective

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:25.027384Z

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Unavailable: canonical work link unavailable.

Observation f3e30caa-33ff-4b82-ab7c-18510a2a0a1d · outbound

This paper cites Dpok: Reinforcement learning for fine-tuning text-to-image diffu- sion models.Advances in Neural Information Processing Systems, 36:79858–79885, 2023.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Dpok: Reinforcement learning for fine-tuning text-to-image diffu- sion models.Advances in Neural Information Processing Systems, 36:79858–79885, 2023

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:25.152338Z

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Observation 8850eb31-6be3-439a-93c4-71f4f9a10364 · outbound

This paper cites Scaling laws for reward model overoptimization.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Scaling laws for reward model overoptimization

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:25.289226Z

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Observation 5184f86d-3863-4887-96cf-3adb84086c7f · outbound

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

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Initno: Boosting text-to-image diffu- sion models via initial noise optimization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:25.420079Z

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Observation 7b4e696d-a53b-4f3a-beda-3bdf545b4049 · outbound

This paper cites Mani- fold preserving guided diffusion.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Mani- fold preserving guided diffusion

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:25.531010Z

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Observation 80d2888a-acfa-4344-a3fb-ad97a137a6a1 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Classifier-Free Diffusion Guidance

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:25.690231Z

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Observation e1cfa2b5-3188-4f51-96be-3d5de8ad1359 · outbound

This paper cites Denoising dif- fusion probabilistic models.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Denoising dif- fusion probabilistic models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:25.780454Z

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Observation a338c08f-6734-47c5-bfdb-9ca1d017a0db · outbound

This paper cites Test- time alignment of diffusion models without reward over- optimisation.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Test- time alignment of diffusion models without reward over- optimisation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:25.937558Z

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Observation 350488ce-b413-4cae-b12c-122a8c5fe4f1 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Adam: A Method for Stochastic Optimization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:26.069050Z

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Unavailable: canonical work link unavailable.

Observation a83aaea3-c7a7-45ee-95cf-71b37fb8be04 · outbound

This paper cites Pick-a-pic: An open dataset of user preferences for text-to-image generation.Ad- vances in neural information processing systems, 36:36652– 36663, 2023.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Pick-a-pic: An open dataset of user preferences for text-to-image generation.Ad- vances in neural information processing systems, 36:36652– 36663, 2023

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:26.268815Z

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Observation 9e4c79f7-5b6b-48c4-88c2-20bbca37be62 · outbound

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

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Aligning Text-to-Image Models using Human Feedback

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:26.393831Z

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Observation 9f30a824-c9e6-4906-ad6f-8b3afa0a7471 · outbound

This paper cites Diffusion-lm improves control- lable text generation.Advances in neural information pro- cessing systems, 35:4328–4343, 2022.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Diffusion-lm improves control- lable text generation.Advances in neural information pro- cessing systems, 35:4328–4343, 2022

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:26.477958Z

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Observation a3a4feaf-3b41-4248-9a9e-486697ab688b · outbound

This paper cites Dynamic Search for Inference-Time Alignment in Diffusion Models.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Dynamic Search for Inference-Time Alignment in Diffusion Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:26.587982Z

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Observation 6aa92c0a-dd19-470b-9e9f-cf1e79b8189a · outbound

This paper cites Null-text inversion for editing real im- ages using guided diffusion models.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Null-text inversion for editing real im- ages using guided diffusion models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:26.699105Z

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Observation f10fa74e-3801-4ed4-9ec6-6ddbe6212c5d · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:26.775235Z

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Observation 63ae9124-ad20-4edb-9b33-ba687af16ae7 · outbound

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

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Aligning Text-to-Image Diffusion Models with Reward Backpropagation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:26.841597Z

Source-reported events for the cited work

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Observation 5392ec5f-36f6-47c6-a7d5-4e7de32486cd · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Learning transferable visual models from natural language supervi- sion

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:26.904311Z

Source-reported events for the cited work

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Observation 7698df61-d7d6-4542-aaaf-0088428df2a4 · outbound

This paper cites Manning, and Chelsea Finn.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Manning, and Chelsea Finn

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:26.986015Z

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Observation e40d25b4-23d4-4049-af73-2c101d69df14 · outbound

This paper cites Test-Time Scaling of Diffusion Models via Noise Trajectory Search.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Test-Time Scaling of Diffusion Models via Noise Trajectory Search

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:27.034362Z

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Observation 4e5e763f-89a2-4448-9dd8-6326d2287a2e · outbound

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

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation High-resolution image syn- thesis with latent diffusion models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:27.102721Z

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Observation 9e5d1960-af34-403f-b77b-1660f584ae0d · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:27.131965Z

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Observation 97369b2e-cec6-4b3f-8bc3-c2ffd8cbd409 · outbound

This paper cites Laion-ai aesthetic predictor (v1): A linear estimator on top of clip to predict the aesthetic quality of pictures.https://github.com/LAION- AI/aesthetic-predictor, 2022.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Laion-ai aesthetic predictor (v1): A linear estimator on top of clip to predict the aesthetic quality of pictures.https://github.com/LAION- AI/aesthetic-predictor, 2022

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:27.388365Z

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Observation 7b3f79a3-849d-4248-a2fb-acfd5e3512bc · outbound

This paper cites Kingma, Ab- hishek Kumar, Stefano Ermon, and Ben Poole.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Kingma, Ab- hishek Kumar, Stefano Ermon, and Ben Poole

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:27.542979Z

Source-reported events for the cited work

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Observation 681c7566-9784-4641-9501-ba3f19e7a050 · outbound

This paper cites Inference-time alignment of diffusion models with direct noise optimization.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Inference-time alignment of diffusion models with direct noise optimization

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:27.779359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bed39288-310a-4503-af62-939ed2137136 · outbound

This paper cites Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:27.940051Z

Source-reported events for the cited work

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Observation a77f0c3a-3325-44af-872e-19c974f19ad0 · outbound

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

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Diffusion model align- ment using direct preference optimization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:28.065028Z

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Observation ea862ac1-7cdd-4f00-9e7c-98bd5639b551 · outbound

This paper cites Practical and asymptotically exact conditional sampling in diffusion models.Advances in Neu- ral Information Processing Systems, 36:31372–31403, 2023.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Practical and asymptotically exact conditional sampling in diffusion models.Advances in Neu- ral Information Processing Systems, 36:31372–31403, 2023

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:28.180694Z

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Observation 14a396cc-86ba-4981-b1f8-6d9d15ad9966 · outbound

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

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Human preference score: Better aligning text- to-image models with human preference

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:28.298906Z

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Observation ddc43f25-dc10-4af0-a4c7-cb46d6785ecc · outbound

This paper cites Dymo: Training-free diffusion model alignment with dynamic multi-objective scheduling.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Dymo: Training-free diffusion model alignment with dynamic multi-objective scheduling

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:28.382751Z

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Observation 16cffbc3-1f10-4304-9c36-e924c4d90f8a · outbound

This paper cites Imagere- ward: Learning and evaluating human preferences for text- to-image generation.Advances in Neural Information Pro- cessing Systems, 36:15903–15935, 2023.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Imagere- ward: Learning and evaluating human preferences for text- to-image generation.Advances in Neural Information Pro- cessing Systems, 36:15903–15935, 2023

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:28.572250Z

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Observation 0bee4c99-ffc8-4728-af35-7e8d161bce40 · outbound

This paper cites Confronting reward overoptimiza- tion for diffusion models: A perspective of inductive and pri- macy biases.

Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation Confronting reward overoptimiza- tion for diffusion models: A perspective of inductive and pri- macy biases

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T20:11:28.708083Z

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Pith citing papers

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