IMMA: Immunizing text-to-image Models against Malicious Adaptation

Advancements in text-to-image models and fine-tuning methods have led to the increasing risk of malicious adaptation, i.e., fine-tuning to generate harmful unauthorized content. Recent works, e.g., Glaze or MIST, have developed data-poisoning techniques which protect the data against adaptation methods. In this work, we consider an alternative paradigm for protection. We propose to ``immunize'' the model by learning model parameters that are difficult for the adaptation methods when fine-tuning malicious content; in short IMMA. Empirical results show IMMA's effectiveness against malicious adaptations, including mimicking the artistic style and learning of inappropriate/unauthorized content, over three adaptation methods: LoRA, Textual-Inversion, and DreamBooth

BloomGML: Graph Machine Learning through the Lens of Bilevel Optimization

Bilevel optimization refers to scenarios whereby the optimal solution of a lower-level energy function serves as input features to an upper-level objective of interest. These optimal features typically depend on tunable parameters of the lower-level energy in such a way that the entire bilevel pipeline can be trained end-to-end. Although not generally presented as such, this paper demonstrates how a variety of graph learning techniques can be recast as special cases of bilevel optimization or simplifications thereof. In brief, building on prior work we first derive a more flexible class of energy functions that, when paired with various descent steps (e.g., gradient descent, proximal methods, momentum, etc.), form graph neural network (GNN) message-passing layers; critically, we also carefully unpack where any residual approximation error lies with respect to the underlying constituent message-passing functions. We then probe several simplifications of this framework to derive close connections with non-GNN-based graph learning approaches, including knowledge graph embeddings, various forms of label propagation, and efficient graph-regularized MLP models. And finally, we present supporting empirical results that demonstrate the versatility of the proposed bilevel lens, which we refer to as BloomGML, referencing that BiLevel Optimization Offers More Graph Machine Learning. Our code is available at https://github.com/amberyzheng/BloomGML. Let graph ML bloom.Comment: Publication at AISTATS 202

Simulating Flow and Dispersion by Using WRF-CFD Coupled Model in a Built-Up Area of Shenyang, China

Results are presented from a series of numerical studies designed to investigate the atmospheric boundary layer structure, ambient wind, and pollutant source location and their impacts on the wind field and pollutant distribution within the built-up areas of Shenyang, China. Two models, namely, Open Source Field Operation and Manipulation (OpenFOAM) software package and Weather Research and Forecasting (WRF) model, are used in the present study. Then the high resolution computational fluid dynamics (CFD) numerical experiments were performed under the typical simulated atmospheric boundary conditions. It was found that the atmospheric boundary structure played a crucial role in the pollution within the building cluster, which determined the potential turbulent diffusion ability of the atmospheric surface layer; the change of the ambient wind direction can significantly affect the dispersion pattern of pollutants, which was a more sensitive factor than the ambient wind speed; under a given atmospheric state, the location of the pollution sources would dramatically determine the pollution patterns within built-up areas. The WRF-CFD numerical evaluation is a reliable method to understand the complicated flow and dispersion within built-up areas

Visual-aural attention modeling for talk show video highlight detection

In this paper, we propose a visual-aural attention modeling based video content analysis approach, which can be used to automatically detect the highlights of the popular TV program - talk show video. First, the visual and aural affective features are extracted to represent and model the human attention of highlight. For efficiency consideration, the adopted affective features are kept as few as possible. Then, a specific fusion strategy called ordinal-decision is used to combine the visual, aural attention models and form the attention curve for a video. This curve can reflect the change of human attention while watching TV. Finally, highlight segments are located at the peaks of the attention curve. Moreover, sentence boundary detection is used to refine the highlight boundaries in order to keep the segments' integrality and fluency. This framework is extensible and flexible in integrating more affective features with a variety of fusion schemes. Experimental results demonstrate our proposed visual-aural attention analysis approach is effective for talk show video highlight detection. ?2008 IEEE.EI

Numerical Study of the Effects of Topography and Urbanization on the Local Atmospheric Circulations over the Beijing-Tianjin-Hebei, China

The effects of the topography and urbanization on the local atmospheric circulations over the Beijing-Tianjin-Hebei (BTH) region were studied by the weather research and forecasting (WRF) model, as well as the interactions among these local atmospheric circulations. It was found that, in the summer day time, the multiscale thermally induced local atmospheric circulations may exist and interact in the same time over the BTH region; the topography played a role in the strengthening of the sea breeze circulations; after sunset, the inland progress of sea breeze was slowed down by the opposite mountain breeze; when the land breeze circulation dominated the Bohai bay, the mountain breeze circulation can couple with the land breeze circulation to form a large circulation ranging from the coastline to the mountains. And the presence of cities cannot change the general state of the sea-land breeze (SLB) circulation and mountain-valley breeze (MVB) circulation but acted to modify these local circulations slightly. Meanwhile, the development of the urban heat island (UHI) circulation was also strongly influenced by the nearby SLB circulation and MVB circulation