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同学你好，非常感谢你对这一系列论文的整理和梳理，真的帮助很大！在阅读文献时注意到，仓库中部分标注为“2024-NeurIPS”的论文是“2023-NeurIPS”。以下是我发现的相关论文列表，供参考：
2023-NeurIPS：[Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularizatio…
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Hello, I am very interested in the experiments of adversarial attacks against pixel diffusion models in the paper. Will the codes be released?
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Hello, I am currently reproducing your paper. Regarding Figure 4, I have some questions that I would like to ask you:
1. Is the dataset Imagene-compatible?
2. Besides DiffAttack, which specific surr…
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Hi Indu,
Thank you for your wonderful work! This work is quite interesting to me and I think the results are amazing. However, I was confused when I tried applying this method to my own dataset. I …
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## 論文タイトル（原文まま）
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
## 一言でいうと
ディフュージョンモデルにおける安全な概念消去（nudityや特定オブジェクトなど）を強化するために、対抗学習（adversarial training…
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Hello, I'm really interested in your work! However, I have some questions about the adversarial attack with text perturbation. In Table 5, the adversarial attack with only perturbation on the text cou…
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Hello,
I am interested in using your DiffAttack on 1D sequences with the aim to make them adversarial against 1D Neural Net classifier (for the specific type of sequences ). I Have a few questions …
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Hi Chen, great work for adversarial attack using diffusion models, I am trying to run your code but getting the following errors:
python main.py --model_name "inception" --save_dir output --images_…
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Thank you for your awesome work.
What should the `placeholder_token` be for the i2p experiment?
Currently, it's ```--placeholder_token="" --initializer_token="art"```, but I'm asking if this is c…
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The inception model I reproduced couldn't do what you did. We usually have 229✖229 as input for that model, here it is 224✖224. does this have any effect please? Looking forward to your reply.