Article

We introduce SplineFlow, a B-spline based flow matching algorithm for modeling complex dynamical systems.

we develop a novel framework for crafting generalizable backdoors in RLHF through emotion-aware trigger synthesis

We propose ContextFlow, a novel context-aware flow matching framework that incorporates prior knowledge to guide the inference of structural tissue dynamics from spatially resolved omics data.

We introduce MASQUE, a diffusion-based framework that generates localized adversarial makeup guided by user-defined text prompts.

We take the first step toward understanding the real-world threats of TDP by studying its generalizability across varying physical conditions.

We propose a structured neural ODE process model to estimate flux and balance samples using gene-expression time-series data

We propose a general framework to craft invisibility cloak for human pose estimation models

We introduce the Weight-Curvature Index (WCI), a novel metric that captures the interplay between model parameters and loss landscape curvature to better understand and improve adversarially robust generalization in deep learning.

We propose AutoDefense, a response-filtering based multi-agent defense framework that filters harmful responses from LLMs.

We propose an availability poisoning attack for generating transferable poisoned data across different victim learners.