AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate | Paper Citation Record

Observation 78442ac1-cf9a-4e8c-9697-b3f8c687b298 · outbound

This paper cites Erasing more than intended? how concept erasure degrades the generation of non-target concepts.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Erasing more than intended? how concept erasure degrades the generation of non-target concepts

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.216828Z

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Observation 058f9b67-6f08-45de-879f-67bc1b8535a5 · outbound

This paper cites Intrinsic dimension of data representations in deep neural networks.Advances in Neural Information Processing Systems, 32.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Intrinsic dimension of data representations in deep neural networks.Advances in Neural Information Processing Systems, 32

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.218524Z

Source-reported events for the cited work

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Observation b5a245b8-ee44-44a1-a6eb-f212d13437ae · outbound

This paper cites Weighted sums of certain dependent random variables.Tohoku Mathematical Journal, Second Series, 19(3):357–367.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Weighted sums of certain dependent random variables.Tohoku Mathematical Journal, Second Series, 19(3):357–367

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.232779Z

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Observation 7992574d-c2ca-480a-bdf2-e53c83de5dce · outbound

This paper cites Cure: Concept unlearning via orthogonal representation editing in diffusion models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Cure: Concept unlearning via orthogonal representation editing in diffusion models

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.200084Z

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Observation a95e23b0-78fc-4be6-9e9f-6b7392ca7936 · outbound

This paper cites Cambridge University Press, 2020.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Cambridge University Press, 2020

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.205849Z

Source-reported events for the cited work

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Observation b11a2e3e-b328-4e81-96cb-d200b5a51f5d · outbound

This paper cites Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-10T09:16:59.488514Z

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Observation ccffc1ff-1f3b-4cf3-8ae6-00ed673e5920 · outbound

This paper cites Distributions of angles in random packing on spheres.Journal of Machine Learning Research, 14(136):1837–1864, 2013.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Distributions of angles in random packing on spheres.Journal of Machine Learning Research, 14(136):1837–1864, 2013

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.152603Z

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Observation 46cf0594-9fc2-44d3-a85c-4aac61dfd930 · outbound

This paper cites Score approximation, estimation and distribution recovery of diffusion models on low-dimensional data.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Score approximation, estimation and distribution recovery of diffusion models on low-dimensional data

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.164407Z

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Observation 1d7e060d-4b97-47f0-b8a2-027840594ede · outbound

This paper cites Improving diffusion models for inverse problems using manifold constraints.Advances in Neural Information Processing Systems, 35:25683–25696.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Improving diffusion models for inverse problems using manifold constraints.Advances in Neural Information Processing Systems, 35:25683–25696

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.230752Z

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Observation dc297187-bb03-4305-a579-972dbda831b7 · outbound

This paper cites SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-10T09:16:59.482591Z

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Observation 5cbdea55-4b97-4663-9849-dda4b3234dcf · outbound

This paper cites Curvature measures.Transactions of the American Mathematical Society, 93(3):418–491.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Curvature measures.Transactions of the American Mathematical Society, 93(3):418–491

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.133549Z

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Observation efb8faf9-e580-4c34-b8c9-e0e8bfe223f7 · outbound

This paper cites Testing the manifold hypothesis.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Testing the manifold hypothesis

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.156696Z

Source-reported events for the cited work

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Observation b992ebf9-8e99-49eb-99d7-820f29ffda40 · outbound

This paper cites Erasing concepts from diffusion models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Erasing concepts from diffusion models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.166248Z

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Observation 40479670-d6be-4803-b52f-53683a5bf49e · outbound

This paper cites The illusion of unlearning: The unstable nature of machine unlearning in text-to-image diffusion models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate The illusion of unlearning: The unstable nature of machine unlearning in text-to-image diffusion models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.234743Z

Source-reported events for the cited work

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Observation 31ea7249-10e7-40bf-9967-f402c323a93c · outbound

This paper cites Continuous Concepts Removal in Text-to-image Diffusion Models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Continuous Concepts Removal in Text-to-image Diffusion Models

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-10T09:16:59.473568Z

Source-reported events for the cited work

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Observation 46a57de0-897e-4996-8e3b-021c45ce09bd · outbound

This paper cites Selective amnesia: A continual learning approach to forgetting in deep generative models.Advances in Neural Information Processing Systems, 36:17170–17194, 2023.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Selective amnesia: A continual learning approach to forgetting in deep generative models.Advances in Neural Information Processing Systems, 36:17170–17194, 2023

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.142155Z

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Observation ddc57014-9729-454f-95ec-841f9b0f37cf · outbound

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

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Prompt-to-Prompt Image Editing with Cross Attention Control

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-07-10T09:16:59.480719Z

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Observation 79ff0756-16fe-4887-a038-d7ec7ea3727c · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.150473Z

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Observation 806172bb-8780-481c-8c7e-8f4924686986 · outbound

This paper cites All but one: Surgical concept erasing with model preservation in text-to-image diffusion models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate All but one: Surgical concept erasing with model preservation in text-to-image diffusion models

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.136440Z

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Observation ee0b26d5-9951-4983-bfcb-300da9fea333 · outbound

This paper cites Manifold interpolating optimal-transport flows for trajectory inference.Advances in neural information processing systems, 35:29705–29718.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Manifold interpolating optimal-transport flows for trajectory inference.Advances in neural information processing systems, 35:29705–29718

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.140410Z

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Observation 1946e2ab-ab74-4a8a-a7d9-d324df6daf3f · outbound

This paper cites Co-occurring associated retained concepts in diffusion unlearning.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Co-occurring associated retained concepts in diffusion unlearning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.170255Z

Source-reported events for the cited work

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Observation ea74ea6a-ea03-476f-aa5c-50cfd922e5c6 · outbound

This paper cites Boosting alignment for post-unlearning text-to-image generative models.Advances in Neural Information Processing Systems, 37:85131–85154, 2024.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Boosting alignment for post-unlearning text-to-image generative models.Advances in Neural Information Processing Systems, 37:85131–85154, 2024

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.189929Z

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Observation 17a0c3e2-5318-4beb-8336-deaea5b9b0a1 · outbound

This paper cites Ablating concepts in text-to-image diffusion models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Ablating concepts in text-to-image diffusion models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.208166Z

Source-reported events for the cited work

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Observation e417ce7f-ea0c-47ae-af70-f992a149125c · outbound

This paper cites Diffusion Models already have a Semantic Latent Space.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Diffusion Models already have a Semantic Latent Space

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-07-10T09:16:59.487922Z

Source-reported events for the cited work

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Observation 87051ba8-3073-49d0-87ec-49c2377c4d0e · outbound

This paper cites Adaptive estimation of a quadratic functional by model selection.Annals of statistics, pages 1302–1338, 2000.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Adaptive estimation of a quadratic functional by model selection.Annals of statistics, pages 1302–1338, 2000

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.183414Z

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Observation ce554d2e-be76-42c0-95ff-f66dbe3828dd · outbound

This paper cites American Mathemati- cal Soc., 2001.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate American Mathemati- cal Soc., 2001

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.148264Z

Source-reported events for the cited work

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Observation 0bea248b-dfee-47f9-854e-935fc2f0cb65 · outbound

This paper cites Localized concept erasure for text-to- image diffusion models using training-free gated low-rank adaptation.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Localized concept erasure for text-to- image diffusion models using training-free gated low-rank adaptation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.148613Z

Source-reported events for the cited work

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Observation e3909f45-ab64-4d55-baef-b7d808f00256 · outbound

This paper cites Localized concept erasure in text-to-image diffusion models via high-level representation misdirection.arXiv preprint arXiv:2602.19631, 2026.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Localized concept erasure in text-to-image diffusion models via high-level representation misdirection.arXiv preprint arXiv:2602.19631, 2026

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-10T09:16:59.483130Z

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Observation 0e27806b-0204-43d3-a3e6-4468faa2a1b2 · outbound

This paper cites Towards resilient safety-driven unlearning for diffusion models against downstream fine-tuning.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Towards resilient safety-driven unlearning for diffusion models against downstream fine-tuning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.150105Z

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Observation f5405696-4206-42cb-a915-9b0d23133b84 · outbound

This paper cites Mace: Mass concept erasure in diffusion models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Mace: Mass concept erasure in diffusion models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.185171Z

Source-reported events for the cited work

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Observation c3bab945-e597-46b6-97f1-1aa1dbaec9f2 · outbound

This paper cites One-dimensional adapter to rule them all: Concepts diffusion models and erasing applications.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate One-dimensional adapter to rule them all: Concepts diffusion models and erasing applications

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.215790Z

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Observation c9ff6de5-688f-439c-916e-74216752fb20 · outbound

This paper cites Finding the homology of submanifolds with high confidence from random samples.Discrete & Computational Geometry, 39(1):419– 441, 2008.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Finding the homology of submanifolds with high confidence from random samples.Discrete & Computational Geometry, 39(1):419– 441, 2008

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.127607Z

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Observation 1178263e-0f5e-4626-abd9-13a6865a5b19 · outbound

This paper cites Diffusion models are minimax optimal distribution estimators.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Diffusion models are minimax optimal distribution estimators

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.228259Z

Source-reported events for the cited work

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Observation b41a41ec-a2a7-48d9-b346-bec056957426 · outbound

This paper cites Leveraging catastrophic forgetting to develop safe diffusion models against malicious finetuning.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Leveraging catastrophic forgetting to develop safe diffusion models against malicious finetuning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.226363Z

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Observation ccc2d877-4f69-49a6-aff6-580e294c1032 · outbound

This paper cites Understanding the latent space of diffusion models through the lens of riemannian geometry.Advances in Neural Information Processing Systems, 36:24129–24142, 2023.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Understanding the latent space of diffusion models through the lens of riemannian geometry.Advances in Neural Information Processing Systems, 36:24129–24142, 2023

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.219259Z

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Observation 37603bb0-201d-4783-ada0-475ee8224ea1 · outbound

This paper cites Direct unlearning optimization for robust and safe text-to-image models.Advances in Neural Information Processing Systems, 37:80244–80267.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Direct unlearning optimization for robust and safe text-to-image models.Advances in Neural Information Processing Systems, 37:80244–80267

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.213146Z

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Observation 0a476ad2-d57b-4d7e-9d94-e4e372ef0216 · outbound

This paper cites Score-based generative models detect manifolds.Advances in Neural Information Processing Systems, 35:35852–35865.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Score-based generative models detect manifolds.Advances in Neural Information Processing Systems, 35:35852–35865

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.220436Z

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Observation 93e4a6ca-a060-4f76-88fc-b0fd2e6fb552 · outbound

This paper cites The intrinsic dimension of images and its impact on learning.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate The intrinsic dimension of images and its impact on learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.217468Z

Source-reported events for the cited work

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Observation 2704fb9f-a8b8-465d-8c8c-29b97731d747 · outbound

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

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate High- resolution image synthesis with latent diffusion models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.213943Z

Source-reported events for the cited work

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Observation 6e8f568a-0949-4401-9c73-5e28a5e83257 · outbound

This paper cites Silhouettes: a graphical aid to the interpretation and validation of cluster analysis.Journal of computational and applied mathematics, 20:53–65.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Silhouettes: a graphical aid to the interpretation and validation of cluster analysis.Journal of computational and applied mathematics, 20:53–65

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.211239Z

Source-reported events for the cited work

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Observation c39fd2a6-f247-4cd0-868d-84f254063520 · outbound

This paper cites Efficient fine-tuning and concept suppression for pruned diffusion models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Efficient fine-tuning and concept suppression for pruned diffusion models

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.196127Z

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Observation a455fa22-8574-4303-9cb1-0c3e00e3a5f7 · outbound

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

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Score-based generative modeling through stochastic differential equations

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.198126Z

Source-reported events for the cited work

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Observation 1d6574d1-36e6-4896-bae5-a432a6cc13d5 · outbound

This paper cites Diffusion models encode the intrinsic dimension of data manifolds.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Diffusion models encode the intrinsic dimension of data manifolds

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.202267Z

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Observation bb69255c-662e-45ef-871d-5ff6c5809777 · outbound

This paper cites Cambridge University Press, 2004.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Cambridge University Press, 2004

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.209300Z

Source-reported events for the cited work

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Observation 7aecec18-dbd9-4163-9327-57dfe9fd7678 · outbound

This paper cites What the daam: Interpreting stable diffusion using cross attention.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate What the daam: Interpreting stable diffusion using cross attention

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.222296Z

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Observation b3dc33c4-1b19-4f03-9968-ddf077269407 · outbound

This paper cites Fine-grained erasure in text-to-image diffusion-based foundation models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Fine-grained erasure in text-to-image diffusion-based foundation models

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.224039Z

Source-reported events for the cited work

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Observation 88b92eca-1c89-489e-9e0f-b7533c441613 · outbound

This paper cites Mass concept erasure in diffusion models with concept hierarchy.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Mass concept erasure in diffusion models with concept hierarchy

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-07-10T09:16:59.473358Z

Source-reported events for the cited work

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Observation c66a4f6d-3306-45b0-a889-bb6091a4be40 · outbound

This paper cites Cambridge university press.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Cambridge university press

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.187079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f1fe276f-6e07-4aa5-887c-df81e1a87b70 · outbound

This paper cites Erasing undesirable influence in diffusion models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Erasing undesirable influence in diffusion models

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.178215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2483e711-9b68-4e78-a580-64d93b38dba7 · outbound

This paper cites Unlearning concepts in diffusion model via concept domain correction and concept preserving gradient.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Unlearning concepts in diffusion model via concept domain correction and concept preserving gradient

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.182144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 26fdac33-7ac2-4977-bf45-76af56790502 · outbound

This paper cites Semantic surgery: Zero-shot concept erasure in diffusion models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Semantic surgery: Zero-shot concept erasure in diffusion models

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-07-10T09:16:59.485838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9e19f4f9-da92-4912-a86f-9166947db6c9 · outbound

This paper cites Forget-me- not: Learning to forget in text-to-image diffusion models.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Forget-me- not: Learning to forget in text-to-image diffusion models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.184154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5c22f3e4-ef1b-4df1-a235-c76d67c543a4 · outbound

This paper cites Concept replacer: Replacing sensitive concepts in diffusion models via precision localization.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Concept replacer: Replacing sensitive concepts in diffusion models via precision localization

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.194171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5850f8fc-73d0-43c9-9db4-cafccd96c601 · outbound

This paper cites grumpy” as an example, which is used in ConAbl, the first anchor-based diffusion unlearning. We collect these manually chosen anchors (including “-.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate grumpy” as an example, which is used in ConAbl, the first anchor-based diffusion unlearning. We collect these manually chosen anchors (including “-

Reference 54

Resolution: malformed identifier; arxiv_id, observed 2026-07-10T09:16:59.491668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cd2fb4c6-b178-4187-9a05-3948891666dd · outbound

This paper cites an unresolved cited work.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-07-10T09:17:00.168259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 23cbdec7-4f43-4923-aa3e-1b2914ec9120 · outbound

This paper cites an unresolved cited work.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-07-10T09:17:00.172162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6adba2b9-1aaf-4c22-8f5a-cfb8d62e7a03 · outbound

This paper cites an unresolved cited work.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-07-10T09:17:00.187386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 996105bb-b448-44fd-887a-0be6e8e4afdd · outbound

This paper cites an unresolved cited work.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-07-10T09:17:00.144097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 28da1d66-2298-4180-a0db-08434d605334 · outbound

This paper cites an unresolved cited work.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-07-10T09:17:00.200247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ae4cdecb-5f96-4ba1-922a-10d3d31a33e8 · outbound

This paper cites an unresolved cited work.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-07-10T09:17:00.203997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7807aa81-905a-4dc2-b485-4a8de5737ae4 · outbound

This paper cites an unresolved cited work.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Unresolved cited work

Reference 61

Resolution: unresolved; raw_fallback, observed 2026-07-10T09:17:00.220847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 06ccff32-7bcb-4fbb-aecd-a1db58904a21 · outbound

This paper cites Mickey Mouse.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Mickey Mouse

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.165475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6b33dd01-d807-48d4-8ff3-11afdc30ae21 · outbound

This paper cites an unresolved cited work.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-07-10T09:17:00.191575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e6bc0937-3844-4929-ba19-802cd0542bc0 · outbound

This paper cites He always dreamed of driving a [MASK] down the Autobahn.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate He always dreamed of driving a [MASK] down the Autobahn

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.162436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6b549af5-f2b9-4b72-bece-217f31b6c85c · outbound

This paper cites Porsche’ itself is also involved, thereby violatingR1. Such violation will be more pronounced in the case of descriptive target concepts,e.g., “grumpy.

AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate Porsche’ itself is also involved, thereby violatingR1. Such violation will be more pronounced in the case of descriptive target concepts,e.g., “grumpy

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T09:17:00.154775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers