1 citations · 1 across the 7 of their papers we have counts for
9 papers
Diffusion Meta-Prompting and Steering for Generalizable Foundation Model Adaptation
Deepak Sridhar, Yi Li, Kartikeya Bhardwaj +7
Prompt learning is a popular method for adapting foundation models, but learned prompts are typically task-specific and fail to generalize to new classes, domains, or compositions…
MED-DSLC: Multi-Expert-Domain Classification via Domain Supervision and Logit Calibration
Zheng Zeng, Deepak Sridhar, Nuno Vasconcelos
Vision-language models (VLMs) such as CLIP enable zero-shot classification by comparing image features with text prompts in a shared embedding space. A fundamental property underly…
Video Reasoning without Training
Deepak Sridhar, Kartikeya Bhardwaj, Jeya Pradha Jeyaraj +3
Video reasoning using Large Multimodal Models (LMMs) relies on costly reinforcement learning (RL) and verbose chain-of-thought, resulting in substantial computational overhead duri…
Diffusion Models with Adaptive Negative Sampling Without External Resources
Alakh Desai, Nuno Vasconcelos
Diffusion models (DMs) have demonstrated an unparalleled ability to create diverse and high-fidelity images from text prompts. However, they are also well-known to vary substantial…
Improving image synthesis with diffusion-negative sampling
Alakh Desai, Nuno Vasconcelos
For image generation with diffusion models (DMs), a negative prompt n can be used to complement the text prompt p, helping define properties not desired in the synthesized image. W…
Adapting Diffusion Models for Improved Prompt Compliance and Controllable Image Synthesis
Deepak Sridhar, Abhishek Peri, Rohith Rachala +1
Recent advances in generative modeling with diffusion processes (DPs) enabled breakthroughs in image synthesis. Despite impressive image quality, these models have various prompt c…
Prompt Sliders for Fine-Grained Control, Editing and Erasing of Concepts in Diffusion Models
Deepak Sridhar, Nuno Vasconcelos
Diffusion models have recently surpassed GANs in image synthesis and editing, offering superior image quality and diversity. However, achieving precise control over attributes in g…
Editable Image Elements for Controllable Synthesis
Jiteng Mu, Michaël Gharbi, Richard Zhang +4
Diffusion models have made significant advances in text-guided synthesis tasks. However, editing user-provided images remains challenging, as the high dimensional noise input space…
SCHEME: Scalable Channel Mixer for Vision Transformers
Deepak Sridhar, Yunsheng Li, Nuno Vasconcelos
Vision Transformers have achieved impressive performance in many vision tasks. While the token mixer or attention block has been studied in great detail, much less research has bee…