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cs.CL2026
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…
eess.IV2026
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…
cs.CL2026
REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations
Buyun Liang, Jinqi Luo, Liangzu Peng +6
Large language models (LLMs) achieve strong performance across many tasks but remain vulnerable to hallucinations, making it important to systematically evaluate their reliability…