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187 results on '"Chang, Ching-Yun"'

1. Translation-Enhanced Multilingual Text-to-Image Generation

Author

Li, Yaoyiran, Chang, Ching-Yun, Rawls, Stephen, Vulić, Ivan, and Korhonen, Anna

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Research on text-to-image generation (TTI) still predominantly focuses on the English language due to the lack of annotated image-caption data in other languages; in the long run, this might widen inequitable access to TTI technology. In this work, we thus investigate multilingual TTI (termed mTTI) and the current potential of neural machine translation (NMT) to bootstrap mTTI systems. We provide two key contributions. 1) Relying on a multilingual multi-modal encoder, we provide a systematic empirical study of standard methods used in cross-lingual NLP when applied to mTTI: Translate Train, Translate Test, and Zero-Shot Transfer. 2) We propose Ensemble Adapter (EnsAd), a novel parameter-efficient approach that learns to weigh and consolidate the multilingual text knowledge within the mTTI framework, mitigating the language gap and thus improving mTTI performance. Our evaluations on standard mTTI datasets COCO-CN, Multi30K Task2, and LAION-5B demonstrate the potential of translation-enhanced mTTI systems and also validate the benefits of the proposed EnsAd which derives consistent gains across all datasets. Further investigations on model variants, ablation studies, and qualitative analyses provide additional insights on the inner workings of the proposed mTTI approaches., Comment: ACL 2023 (Main)

Published
2023
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2. Cross-lingual Alignment Methods for Multilingual BERT: A Comparative Study

Author

Kulshreshtha, Saurabh, Redondo-García, José Luis, and Chang, Ching-Yun

Subjects
Computer Science - Computation and Language
Abstract

Multilingual BERT (mBERT) has shown reasonable capability for zero-shot cross-lingual transfer when fine-tuned on downstream tasks. Since mBERT is not pre-trained with explicit cross-lingual supervision, transfer performance can further be improved by aligning mBERT with cross-lingual signal. Prior work proposes several approaches to align contextualised embeddings. In this paper we analyse how different forms of cross-lingual supervision and various alignment methods influence the transfer capability of mBERT in zero-shot setting. Specifically, we compare parallel corpora vs. dictionary-based supervision and rotational vs. fine-tuning based alignment methods. We evaluate the performance of different alignment methodologies across eight languages on two tasks: Name Entity Recognition and Semantic Slot Filling. In addition, we propose a novel normalisation method which consistently improves the performance of rotation-based alignment including a notable 3% F1 improvement for distant and typologically dissimilar languages. Importantly we identify the biases of the alignment methods to the type of task and proximity to the transfer language. We also find that supervision from parallel corpus is generally superior to dictionary alignments., Comment: Accepted as a long paper in Findings of EMNLP 2020

Published
2020

8. Transformations for linguistic steganography

Author

Chang, Ching-Yun and Clark, Stephen

Subjects
004, Linguistic steganography
Abstract

Linguistic steganography is a form of covert communication using natural language to conceal the existence of the hidden message. It is usually achieved by systematically making changes to a cover text, such that the manipulations, namely the very act of communication, are undetectable to an outside observer (human or computer). In this thesis, we explore three possible linguistic transformations - lexical substitution, adjective deletion and word ordering - which are able to generate alternatives for a cover text. For each transformation, we propose different transformation checkers in order to certify the naturalness of a modified sentence. Our lexical substitution checkers are based on contextual n-gram counts and the αskew divergence of those counts derived from the Google n-gram corpus. For adjective deletion, we propose an n-gram count method similar to the substitution n-gram checker and a support vector machine classifier using n-gram counts and other measures to classify deletable and undeletable adjectives in context. As for word ordering, we train a maximum entropy classifier using some syntactic features to determine the naturalness of a sentence permutation. The proposed transformation checkers were evaluated by human judged data, and the evaluation results are presented using precision and recall curves. The precision and recall of a transformation checker can be interpreted as the security level and the embedding capacity of the stegosystem, respectively. The results show that the proposed transformation checkers can provide a confident security level and reasonable embedding capacity for the steganography application. In addition to the transformation checkers, we demonstrate possible data encoding methods for each of the linguistic transformations. For lexical substitution, we propose a novel encoding method based on vertex colouring. For adjective deletion, we not only illustrate its usage in the steganography application, but also show that the adjective deletion technique can be applied to a secret sharing scheme, where the secret message is encoded in two different versions of the carrier text, with different adjectives deleted in each version. For word ordering, we propose a ranking-based encoding method and also show how the technique can be integrated into existing translation based embedding methods.

Published
2013
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10. Targeted Proteomics of the Eicosanoid Biosynthetic Pathway Completes an Integrated Genomics-Proteomics-Metabolomics Picture of Cellular Metabolism*

Author

Sabidó, Eduard, Quehenberger, Oswald, Shen, Qin, Chang, Ching-Yun, Shah, Ishita, Armando, Aaron M, Andreyev, Alexander, Vitek, Olga, Dennis, Edward A, and Aebersold, Ruedi

Subjects
Analytical Chemistry, Biochemistry and Cell Biology, Biomedical and Clinical Sciences, Biological Sciences, Chemical Sciences, Medical Biochemistry and Metabolomics, Human Genome, Biotechnology, Genetics, 2.1 Biological and endogenous factors, Aetiology, Adenosine Triphosphate, Animals, Arachidonic Acid, Biosynthetic Pathways, Cell Line, Eicosanoids, Inflammation, Lipid Metabolism, Lipopolysaccharides, Macrophages, Mass Spectrometry, Metabolomics, Mice, Proteomics, Signal Transduction, Biochemistry & Molecular Biology
Abstract

Eicosanoids constitute a diverse class of bioactive lipid mediators that are produced from arachidonic acid and play critical roles in cell signaling and inflammatory aspects of numerous diseases. We have previously quantified eicosanoid metabolite production in RAW264.7 macrophage cells in response to Toll-like receptor 4 signaling and analyzed the levels of transcripts coding for the enzymes involved in the eicosanoid metabolite biosynthetic pathways. We now report the quantification of changes in protein levels under similar experimental conditions in RAW264.7 macrophages by multiple reaction monitoring mass spectrometry, an accurate targeted protein quantification method. The data complete the first fully integrated genomic, proteomic, and metabolomic analysis of the eicosanoid biochemical pathway.

Published
2012

13. Image Data Hiding Schemes Based on Graph Coloring

Author

Yue, Shuai, Wang, Zhi-Hui, Chang, Ching-Yun, Chang, Chin-Chen, Li, Ming-Chu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Hsu, Ching-Hsien, editor, Yang, Laurence T., editor, Ma, Jianhua, editor, and Zhu, Chunsheng, editor

Published
2011
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15. Interleukin-33 antibody failed to demonstrate benefit in a phase II, double-blind, randomized, placebo-controlled study in adult patients with moderate-to-severe atopic dermatitis

Author

Laquer, Vivian, primary, Parra, Viviana, additional, Lacour, Jean-Philippe, additional, Takahashi, Hidetoshi, additional, Knorr, Jack, additional, Okragly, Angela J., additional, James, Douglas E., additional, Sims, Jonathan T., additional, Chang, Ching-Yun, additional, Chao, Jeannie, additional, and Klekotka, Paul, additional

Published
2022
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16. Additional file 1 of Relationship between gene expression patterns from nasopharyngeal swabs and serum biomarkers in patients hospitalized with COVID-19, following treatment with the neutralizing monoclonal antibody bamlanivimab

Author

Sims, Jonathan T., Poorbaugh, Josh, Chang, Ching-Yun, Holzer, Timothy R., Zhang, Lin, Engle, Sarah M., Beasley, Stephanie, Doman, Thompson N., Naughton, Lynn, Higgs, Richard E., Kallewaard, Nicole, and Benschop, Robert J.

Abstract

Additional file 1. Supplementary figures and methods.

Published
2022
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17. Longitudinal Assessment of Systemic Steroid Therapy on Hyperinflammatory Endothelial Biomarker Profiles and Serology Responses of COVID-19 Patients

Author

Sims, Jonathan Thomas, primary, Chang, Ching-Yun, additional, Poorbaugh, Josh, additional, Daniels, Montanea, additional, Beasley, Stephanie, additional, Zhang, Lin, additional, Rodgers, George, additional, Lena, Fabio, additional, Lacerenza, Leonardo, additional, Sposato, Bruno, additional, Dupont, Annabelle, additional, Susen, Sophie, additional, Casalini, Giacomo, additional, Corbellino, Mario, additional, Stebbing, Justin, additional, and Krishnan, Venkatesh, additional

Published
2022
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20. Preschool Teachers’ Attitudes towards Inclusive Education: A Survey in Indonesia and Taiwan

Author

Wu Chi Cheng, Salim Herli, Chang Ching Yun, and Chano Jiraporn

Subjects
General Medicine
Abstract

The study measures the attitudes of preschool teachers towards inclusive education in Taiwan and Indonesia with the Scale of Preschool Teachers’ Attitudes towards Inclusion (SPTAI). A total of 637 participants (Indonesian = 233 and Taiwan = 404) participated in the survey. SPATI, developed in the study, was composed of 18 items, designated in a five-point Likert Scale with a response spanning from “strongly disagree (1)” to “strongly agree (5)”. Four factors were extracted from SPTAI via exploratory factor analysis which explained 62.56% of the variance. Cronbach’s alpha for the overall scale was .93 and coefficients for the four factors were .83, .84, .82, and .70, respectively. Overall, the average scores of SPATI in Indonesia and Taiwan were 3.65 and 3.20, which exceeded the mid-point of 3.0; and the difference between the two countries was statistically significant (t = 10.98, p < .001). Results indicated that the preschool teachers in Indonesia stood between “neutral” and “somewhat agree” with leaning towards the latter. The “Taiwan preschool teachers upheld positive attitudes of inclusive education but yet their stance was more “neutral”. Significantly, Indonesian teachers were even more favourable to inclusive education than their Taiwanese counterparts. Several reasons that might explain the difference between these two countries are discussed in the study.

Published
2022

24. Insights into adult atopic dermatitis heterogeneity derived from circulating biomarker profiling in patients with moderate‐to‐severe disease

Author

Sims, Jonathan T., primary, Chang, Ching‐Yun, additional, Higgs, Richard E., additional, Engle, Sarah M., additional, Liu, Yushi, additional, Sissons, Sean E., additional, Rodgers, George H., additional, Simpson, Eric L., additional, Silverberg, Jonathan I., additional, Forman, Seth B., additional, Janes, Jonathan M., additional, Colvin, Stephanie C., additional, and Guttman‐Yassky, Emma, additional

Published
2021
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26. Characterization of the cytokine storm reflects hyperinflammatory endothelial dysfunction in COVID-19

Author

Sims, Jonathan T., primary, Krishnan, Venkatesh, additional, Chang, Ching-Yun, additional, Engle, Sarah M., additional, Casalini, Giacomo, additional, Rodgers, George H., additional, Bivi, Nicoletta, additional, Nickoloff, Brian J., additional, Konrad, Robert J., additional, de Bono, Stephanie, additional, Higgs, Richard E., additional, Benschop, Robert J., additional, Ottaviani, Silvia, additional, Cardoso, Anabela, additional, Nirula, Ajay, additional, Corbellino, Mario, additional, and Stebbing, Justin, additional

Published
2021
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30. Predictive biomarker modeling of pediatric atopic dermatitis severity based on longitudinal serum collection.

Author

Engle, Sarah M, Chang, Ching-Yun, Ulrich, Benjamin J, Satterwhite, Allyson, Hayes, Tristan, Robling, Kim, Sissons, Sean E, Schmitz, Jochen, Tepper, Robert S, Kaplan, Mark H, and Sims, Jonathan T

Subjects
*ATOPIC dermatitis, *MONONUCLEAR leukocytes, *PREDICTION models
Abstract

The pathogenesis of atopic dermatitis (AD) results from complex interactions between environmental factors, barrier defects, and immune dysregulation resulting in systemic inflammation. Therefore, we sought to characterize circulating inflammatory profiles in pediatric AD patients and identify potential signaling nodes which drive disease heterogeneity and progression. We analyzed a sample set of 87 infants that were at high risk for atopic disease based on AD diagnoses. Clinical parameters, serum, and peripheral blood mononuclear cells (PBMCs) were collected upon entry, and at 1 and 4 years later. Within patient serum, 126 unique analytes were measured using a combination of multiplex platforms and ultrasensitive immunoassays. We assessed the correlation of inflammatory analytes with AD severity (SCORAD). Key biomarkers, such as IL-13 (rmcorr = 0.47) and TARC/CCL17 (rmcorr = 0.37), among other inflammatory signals, significantly correlated with SCORAD across all timepoints in the study. Flow cytometry and pathway analysis of these analytes implies that CD4 T-cell involvement in type 2 immune responses was enhanced at the earliest time point (year 1) relative to the end of study collection (year 5). Importantly, forward selection modeling identified 18 analytes in infant serum at study entry which could be used to predict change in SCORAD 4 years later. We have identified a pediatric AD biomarker signature linked to disease severity which will have predictive value in determining AD persistence in youth and provide utility in defining core systemic inflammatory signals linked to pathogenesis of atopic disease. [ABSTRACT FROM AUTHOR]

Published
2022
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38. A Targeted Mass Spectrometry Strategy for Developing Proteomic Biomarkers: A Case Study of Epithelial Ovarian Cancer

Author

Hüttenhain, Ruth, primary, Choi, Meena, additional, Martin de la Fuente, Laura, additional, Oehl, Kathrin, additional, Chang, Ching-Yun, additional, Zimmermann, Anne-Kathrin, additional, Malander, Susanne, additional, Olsson, Håkan, additional, Surinova, Silvia, additional, Clough, Timothy, additional, Heinzelmann-Schwarz, Viola, additional, Wild, Peter J., additional, Dinulescu, Daniela M., additional, Niméus, Emma, additional, Vitek, Olga, additional, and Aebersold, Ruedi, additional

Published
2019
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48. Reproducible and consistent quantification of the Saccharomyces cerevisiae proteome by SWATH-mass spectrometry

Author

Selevsek, Nathalie, Chang, Ching-Yun, Gillet, Ludovic C, Navarro, Pedro, Bernhardt, Oliver M, Reiter, Lukas, Cheng, Lin-Yang, Vitek, Olga, Aebersold, Ruedi, Selevsek, Nathalie, Chang, Ching-Yun, Gillet, Ludovic C, Navarro, Pedro, Bernhardt, Oliver M, Reiter, Lukas, Cheng, Lin-Yang, Vitek, Olga, and Aebersold, Ruedi

Abstract

Targeted mass spectrometry by selected reaction monitoring (S/MRM) has proven to be a suitable technique for the consistent and reproducible quantification of proteins across multiple biological samples and a wide dynamic range. This performance profile is an important prerequisite for systems biology and biomedical research. However, the method is limited to the measurements of a few hundred peptides per LC-MS analysis. Recently, we introduced SWATH-MS, a combination of data independent acquisition and targeted data analysis that vastly extends the number of peptides/proteins quantified per sample, while maintaining the favorable performance profile of S/MRM. Here we applied the SWATH-MS technique to quantify changes over time in a large fraction of the proteome expressed in Saccharomyces cerevisiae in response to osmotic stress. We sampled cell cultures in biological triplicates at six time points following the application of osmotic stress and acquired single injection data independent acquisition data sets on a high-resolution 5600 tripleTOF instrument operated in SWATH mode. Proteins were quantified by the targeted extraction and integration of transition signal groups from the SWATH-MS datasets for peptides that are proteotypic for specific yeast proteins. We consistently identified and quantified more than 15,000 peptides and 2500 proteins across the 18 samples. We demonstrate high reproducibility between technical and biological replicates across all time points and protein abundances. In addition, we show that the abundance of hundreds of proteins was significantly regulated upon osmotic shock, and pathway enrichment analysis revealed that the proteins reacting to osmotic shock are mainly involved in the carbohydrate and amino acid metabolism. Overall, this study demonstrates the ability of SWATH-MS to efficiently generate reproducible, consistent, and quantitatively accurate measurements of a large fraction of a proteome across multiple samples.

Published
2015

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