140 citations · 148 across the 9 of their papers we have counts for
13 papers
FastGuide: Accelerating Reward Guidance for Diffusion Large Language Models
Darshan Thaker, Lachlan Ewen MacDonald, René Vidal
Gradient-based reward guidance provides a flexible way to use downstream reward models to control masked diffusion language models at inference time. However, its computational cos…
ANaLOG: Anisotropic Native-Latent Operator Guidance for Solving Inverse Problems
Darshan Thaker, Lachlan Ewen MacDonald, René Vidal
Native-latent guidance is a recent paradigm for solving inverse problems with latent diffusion models. It replaces repeated evaluations of the image-space forward model, each requi…
Scale-Cascaded Diffusion Models for Super-Resolution in Medical Imaging
Darshan Thaker, Mahmoud Mostapha, Radu Miron +2
Diffusion models have been increasingly used as strong generative priors for solving inverse problems such as super-resolution in medical imaging. However, these approaches typical…
SECA: Semantically Equivalent and Coherent Attacks for Eliciting LLM Hallucinations
Buyun Liang, Liangzu Peng, Jinqi Luo +3
Large Language Models (LLMs) are increasingly deployed in high-risk domains. However, state-of-the-art LLMs often exhibit hallucinations, raising serious concerns about their relia…
KDA: A Knowledge-Distilled Attacker for Generating Diverse Prompts to Jailbreak LLMs
Buyun Liang, Kwan Ho Ryan Chan, Darshan Thaker +2
Jailbreak attacks exploit specific prompts to bypass LLM safeguards, causing the LLM to generate harmful, inappropriate, and misaligned content. Current jailbreaking methods rely h…
Frequency-Guided Posterior Sampling for Diffusion-Based Image Restoration
Darshan Thaker, Abhishek Goyal, René Vidal
Image restoration aims to recover high-quality images from degraded observations. When the degradation process is known, the recovery problem can be formulated as an inverse proble…