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Shruti Agarwal

7 accepted papers

2026

Interpretable Prompts made Edit-Friendly: Token-to-Token Similarity Reduction in dLLMs for Edit-Friendly Hard Prompt Inversion

CVPR 2026

Crafting prompts via Prompt Engineering that steer a model's internal representations toward specific and pre-defined outcomes can be time-consuming, often requiring multiple iterations. Hard Prompt Inversion offers a complementary workflow: start from a reference image and generate a prompt that co

Cited by 0SourceScholar
2026

TokenTrace: Multi-Concept Attribution through Watermarked Token Recovery

CVPR 2026

Generative AI models pose a significant challenge to intellectual property (IP), as they can replicate unique artistic styles and concepts without attribution. While watermarking offers a potential solution, existing methods often fail in complex scenarios where multiple concepts (e.g., an object an

Cited by 0SourceScholar
2025

On the Coexistence and Ensembling of Watermarks

NeurIPS 2025poster

Watermarking, the practice of embedding imperceptible information into media such as images, videos, audio, and text, is essential for intellectual property protection, content provenance and attribution. The growing complexity of digital ecosystems necessitates watermarks for different uses to be e…

Cited by 0SourceScholar
2025

TrustMark: Robust Watermarking and Watermark Removal for Arbitrary Resolution Images

ICCV 2025poster

Imperceptible digital watermarking is important in copyright protection, misinformation prevention, and responsible generative AI. We propose TrustMark - a watermarking method that leverages a spatio-spectral loss function and a 1x1 convolution layer to enhance encoding quality. TrustMark is robust…

2025

Your Text Encoder Can Be An Object-Level Watermarking Controller

ICCV 2025poster

Invisible watermarking of AI-generated images can help with copyright protection, enabling detection and identification of AI-generated media. In this work, we present a novel approach to watermark images of T2I Latent Diffusion Models (LDMs). By only fine-tuning text token embeddings \mathcal W _*,…

2024

ProMark: Proactive Diffusion Watermarking for Causal Attribution

CVPR 2024poster

Generative AI (GenAI) is transforming creative workflows through the capability to synthesize and manipulate images via high-level prompts. Yet creatives are not well supported to receive recognition or reward for the use of their content in GenAI training. To this end we propose ProMark a causal at…

Cited by 14SourcePDFScholar