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Anubhav Jain

@anubhavj480.bsky.social
96 followers 50 following 25 posts

PhD Candidate @ NYU

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Reposted by Anubhav Jain
Julian Togelius @togelius.bsky.social · 30/04/2025
New results from @anubhavj480.bsky.social, one of my co-advised students (on the job market, hint hint): a new way of forging or removing watermarks in images generated with diffusion models. This is a simple and effective adversarial attack that only requires only one example!
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Anubhav Jain @anubhavj480.bsky.social · 30/04/2025
Think your latent-noise diffusion watermarking method is robust? Think again! We show that they are susceptible to simple adversarial attacks that only require one watermarked example and an off-the-shelf encoder. This attack can forge and remove the watermark with very high accuracy.
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Anubhav Jain @anubhavj480.bsky.social · 18/12/2024
Diffusion models are amazing at generating high-quality images of what you ask them for, but can also generate things you didn't ask for. How do you stop a diffusion model from generating unwanted content such as nudity, violence, or the style of a particular artist? We introduce TraSCE (1/n)
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Anubhav Jain @anubhavj480.bsky.social · 04/12/2024
Have you ever wondered why diffusion models memorize and all initializations lead to the same training sample? As we show, this is because like in dynamic systems, the memorized sample acts as an attractor and a corresponding attraction basin is formed in the denoising trajectory.
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