Generating Valid and Natural Adversarial Examples with Large Language Models

Deep learning-based natural language processing (NLP) models, particularly pre-trained language models (PLMs), have been revealed to be vulnerable to adversarial attacks. However, the adversarial examples generated by many mainstream word-level adversarial attack models are neither valid nor natural, leading to the loss of semantic maintenance, grammaticality, and human imperceptibility. Based on the exceptional capacity of language understanding and generation of large language models (LLMs), we propose LLM-Attack, which aims at generating both valid and natural adversarial examples with LLMs. The method consists of two stages: word importance ranking (which searches for the most vulnerable words) and word synonym replacement (which substitutes them with their synonyms obtained from LLMs). Experimental results on the Movie Review (MR), IMDB, and Yelp Review Polarity datasets against the baseline adversarial attack models illustrate the effectiveness of LLM-Attack, and it outperforms the baselines in human and GPT-4 evaluation by a significant margin. The model can generate adversarial examples that are typically valid and natural, with the preservation of semantic meaning, grammaticality, and human imperceptibility.Comment: Submitted to the IEEE for possible publicatio

Learngene: Inheriting Condensed Knowledge from the Ancestry Model to Descendant Models

During the continuous evolution of one organism's ancestry, its genes accumulate extensive experiences and knowledge, enabling newborn descendants to rapidly adapt to their specific environments. Motivated by this observation, we propose a novel machine learning paradigm Learngene to enable learning models to incorporate three key characteristics of genes. (i) Accumulating: the knowledge is accumulated during the continuous learning of an ancestry model. (ii) Condensing: the extensive accumulated knowledge is condensed into a much more compact information piece, i.e., learngene. (iii) Inheriting: the condensed learngene is inherited to make it easier for descendant models to adapt to new environments. Since accumulating has been studied in well-established paradigms like large-scale pre-training and lifelong learning, we focus on condensing and inheriting, which induces three key issues and we provide the preliminary solutions to these issues in this paper: (i) Learngene Form: the learngene is set to a few integral layers that can preserve significance. (ii) Learngene Condensing: we identify which layers among the ancestry model have the most similarity as one pseudo descendant model. (iii) Learngene Inheriting: to construct distinct descendant models for the specific downstream tasks, we stack some randomly initialized layers to the learngene layers. Extensive experiments across various settings, including using different network architectures like Vision Transformer (ViT) and Convolutional Neural Networks (CNNs) on different datasets, are carried out to confirm four advantages of Learngene: it makes the descendant models 1) converge more quickly, 2) exhibit less sensitivity to hyperparameters, 3) perform better, and 4) require fewer training samples to converge

Photocatalytic TiO2/rGO/CuO Composite for Wastewater Treatment of Cr(VI) Under Visible Light

The harm of chromium pollution to the environment has caused a widespread concern; hexavalent chromium is a toxic, cancerogenic, and genetically mutagenic contaminant to the human body; by contrast, trivalent chromium is almost non-toxic to the human body; therefore, it is a feasible method to reduce hexavalent chromium to trivalent chromium. Photocatalysis is a new environmentally friendly and harmless technology, which can transform pollutants into non-toxic or less toxic products. In this study, we synthesized TiO2/rGO/CuO ternary nanocomposites to treat hexavalent chromium pollution under visible light. Under optimal conditions, the photoreduction efficiency of 100 ppm hexavalent chromium solution could reach 100% in 80 min. The photoreduction rate of hexavalent chromium is 29.4 times than that of pure TiO2. The photocatalytic property of CuO in TG2C8 nanocomposites is attributed to accelerate the separation of electrons and holes and the efficient electron transfer through the rGO framework. We believe that TiO2/rGO/CuO composites have great potential in wastewater treatment.publishedVersio

Changes and analysis of transvaginal forceps delivery rate in primary hospitals in the past 10 years

Objectives: This study analyzed the changes of vaginal forceps delivery rate in Jiading Maternal and Child Health Hospitalin the past 10 years in order to provide theoretical reference for reducing the rate of cesarean section and solving cephalicdystocia.Material and methods: The basic information, delivery means and vaginal forceps indication of 78,811 parturients whogave birth in our hospital between January 1, 2009 to December 31, 2018 were analyzed retrospectively, and statisticalanalysis was carried out by analysis of variance and Chi-square test.Results: In the past 10 years, there was a significant difference in the rate of vaginal forceps use among different years(p < 0. 05). With 2014 as the turning point, the rate of forceps use increased the fastest, from 0.7% in 2013 to 3.3% in2016. The main indications of forceps increased use in our hospital from high to low were fetal distress, abnormal occipitalposition, prolongation of the second stage of labor and shortening of the second stage of labor. And there was significantdifference among different years (p < 0.000). Although there was no significant difference among the years of labor forcepsuse in patients with prolonged second stage of labor and abnormal occipital position (p > 0.05), the proportion of forcepsdelivery in the second stage of labor was gradually decreased with 2014 as the dividing line. Although there was significantdifference among the patients who shortened the second stage of labor (X2 = 23,886, p < 0.01), it ranked fourth all the time.Conclusions: In the past 10 years, the rate of forceps use has been on the rise. With the implementation of the new stage oflabor and painless delivery in 2014, vaginal forceps have become the main means to solve the problem of cephalic dystocia

Context Does Matter: End-to-end Panoptic Narrative Grounding with Deformable Attention Refined Matching Network

Panoramic Narrative Grounding (PNG) is an emerging visual grounding task that aims to segment visual objects in images based on dense narrative captions. The current state-of-the-art methods first refine the representation of phrase by aggregating the most similar $k$ image pixels, and then match the refined text representations with the pixels of the image feature map to generate segmentation results. However, simply aggregating sampled image features ignores the contextual information, which can lead to phrase-to-pixel mis-match. In this paper, we propose a novel learning framework called Deformable Attention Refined Matching Network (DRMN), whose main idea is to bring deformable attention in the iterative process of feature learning to incorporate essential context information of different scales of pixels. DRMN iteratively re-encodes pixels with the deformable attention network after updating the feature representation of the top-$k$ most similar pixels. As such, DRMN can lead to accurate yet discriminative pixel representations, purify the top-$k$ most similar pixels, and consequently alleviate the phrase-to-pixel mis-match substantially.Experimental results show that our novel design significantly improves the matching results between text phrases and image pixels. Concretely, DRMN achieves new state-of-the-art performance on the PNG benchmark with an average recall improvement 3.5%. The codes are available in: https://github.com/JaMesLiMers/DRMN.Comment: Accepted by ICDM 202

ShanshuiDaDA: An Interactive, Generative System towards Chinese Shanshui Painting

Shanshui, which means mountain and water, is an East Asian traditional brush painting involving natural landscapes. This paper proposes an interactive and generative system based on a Generative Adversarial Network(GAN), which helps users draw Shanshui easily. We name this system and installation ShanshuiDaDA. ShanshuiDaDA is trained with CycleGAN and wrapped with a web-based interface. When participants scribble lines and sketch the landscape, the ShanshuiDaDA will assist them in generating and creating a Chinese "Shanshui" painting in real time.Comment: 4 pages, Machine Learning for Creativity and Design Workshop, the 32nd Conference on Neural Information Processing Systems (NIPS 2018), Montreal, Canada. See: https://nips2018creativity.github.io/doc/shanshui_dada.pd

Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation

Single-source domain generalization (SDG) in medical image segmentation is a challenging yet essential task as domain shifts are quite common among clinical image datasets. Previous attempts most conduct global-only/random augmentation. Their augmented samples are usually insufficient in diversity and informativeness, thus failing to cover the possible target domain distribution. In this paper, we rethink the data augmentation strategy for SDG in medical image segmentation. Motivated by the class-level representation invariance and style mutability of medical images, we hypothesize that unseen target data can be sampled from a linear combination of $C$ (the class number) random variables, where each variable follows a location-scale distribution at the class level. Accordingly, data augmented can be readily made by sampling the random variables through a general form. On the empirical front, we implement such strategy with constrained B$\acute{\rm e}$zier transformation on both global and local (i.e. class-level) regions, which can largely increase the augmentation diversity. A Saliency-balancing Fusion mechanism is further proposed to enrich the informativeness by engaging the gradient information, guiding augmentation with proper orientation and magnitude. As an important contribution, we prove theoretically that our proposed augmentation can lead to an upper bound of the generalization risk on the unseen target domain, thus confirming our hypothesis. Combining the two strategies, our Saliency-balancing Location-scale Augmentation (SLAug) exceeds the state-of-the-art works by a large margin in two challenging SDG tasks. Code is available at https://github.com/Kaiseem/SLAug

Impact of dietary manganese on intestinal barrier and inflammatory response in broilers challenged with Salmonella Typhimurium

Growing concern for public health and food safety has prompted a special interest in developing nutritional strategies for removing waterborne and foodborne pathogens, including Salmonella. Strong links between manganese (Mn) and intestinal barrier or immune function hint that dietary Mn supplementation is likely to be a promising approach to limit the loads of pathogens in broilers. Here, we provide evidence that Salmonella Typhimurium (S. Typhimurium, 4 × 108 CFUs) challenge-induced intestinal injury along with systemic Mn redistribution in broilers. Further examining of the effect of dietary Mn treatments (a basal diet plus additional 0, 40, or 100 mg Mn/kg for corresponding to Mn-deficient, control, or Mn-surfeit diet, respectively) on intestinal barrier and inflammation status of broilers infected with S. Typhimurium revealed that birds fed the control and Mn-surfeit diets exhibited improved intestinal tight junctions and microbiota composition. Even without Salmonella infection, dietary Mn deficiency alone increased intestinal permeability by impairing intestinal tight junctions. In addition, when fed the control and Mn-surfeit diets, birds showed decreased Salmonella burdens in cecal content and spleen, with a concomitant increase in inflammatory cytokine levels in spleen. Furthermore, the dietary Mn-supplementation-mediated induction of cytokine production was probably associated with the nuclear factor kappa-B (NF-κB)/hydrogen peroxide (H2O2) pathway, as judged by the enhanced manganese superoxide dismutase activity and the increased H2O2 level in mitochondria, together with the increased mRNA level of NF-κB in spleen. Ingenuity-pathway analysis indicated that acute-phase response pathways, T helper type 1 pathway, and dendritic cell maturation were significantly activated by the dietary Mn supplementation. Our data suggest that dietary Mn supplementation could enhance intestinal barrier and splenic inflammatory response to fight against Salmonella infection in broilers