Naresh Kumar Devulapally — accepted AI-conference papers

2026

Forget Less by Learning from Parents Through Hierarchical Relationships

Arjun Ramesh Kaushik, Naresh Kumar Devulapally, Vishnu Suresh Lokhande, Nalini K. Ratha, Venu Govindaraju

AAAI 2026technical

Custom Diffusion Models (CDMs) offer impressive capabilities for personalization in generative modeling, yet they remain vulnerable to catastrophic forgetting when learning new concepts sequentially. Existing approaches primarily focus on minimizing interference between concepts, often neglecting th

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2026

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

Naresh Kumar Devulapally, Shruti Agarwal, Vishal Asnani, Vishnu Suresh Lokhande

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

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2025

Your Text Encoder Can Be An Object-Level Watermarking Controller

Naresh Kumar Devulapally, Mingzhen Huang, Vishal Asnani, Shruti Agarwal, Siwei Lyu, Vishnu Suresh Lokhande

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 _*,…

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