Search Results for author: Ying Xu

Found 35 papers, 7 papers with code

UIBert: Learning Generic Multimodal Representations for UI Understanding

1 code implementation29 Jul 2021 Chongyang Bai, Xiaoxue Zang, Ying Xu, Srinivas Sunkara, Abhinav Rastogi, Jindong Chen, Blaise Aguera y Arcas

Our key intuition is that the heterogeneous features in a UI are self-aligned, i. e., the image and text features of UI components, are predictive of each other.

StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement

1 code implementation13 Feb 2022 Zheng Zhang, Ying Xu, Yanhao Wang, Bingsheng Yao, Daniel Ritchie, Tongshuang Wu, Mo Yu, Dakuo Wang, Toby Jia-Jun Li

Despite its benefits for children's skill development and parent-child bonding, many parents do not often engage in interactive storytelling by having story-related dialogues with their child due to limited availability or challenges in coming up with appropriate questions.

Chatbot

Analyzing Fairness in Deepfake Detection With Massively Annotated Databases

3 code implementations11 Aug 2022 Ying Xu, Philipp Terhörst, Kiran Raja, Marius Pedersen

In this work, we investigate factors causing biased detection in public Deepfake datasets by (a) creating large-scale demographic and non-demographic attribute annotations with 47 different attributes for five popular Deepfake datasets and (b) comprehensively analysing attributes resulting in AI-bias of three state-of-the-art Deepfake detection backbone models on these datasets.

Attribute Decision Making +3

Learning Pairwise Interaction for Generalizable DeepFake Detection

1 code implementation26 Feb 2023 Ying Xu, Kiran Raja, Luisa Verdoliva, Marius Pedersen

We obtain 98. 48% BOSC accuracy on the FF++ dataset and 90. 87% BOSC accuracy on the CelebDF dataset suggesting a promising direction for generalization of DeepFake detection.

Decision Making DeepFake Detection +2

Event-based Feature Extraction Using Adaptive Selection Thresholds

no code implementations18 Jul 2019 Saeed Afshar, Ying Xu, Jonathan Tapson, André van Schaik, Gregory Cohen

A novel heuristic method for network size selection is proposed which makes use of noise events and their feature representations.

Benchmarking

Learning over inherently distributed data

no code implementations30 Jul 2019 Donghui Yan, Ying Xu

This framework only requires a small amount of local signatures to be shared among distributed sites, eliminating the need of having to transmitting big data.

Distributed Computing

Similarity Kernel and Clustering via Random Projection Forests

no code implementations28 Aug 2019 Donghui Yan, Songxiang Gu, Ying Xu, Zhiwei Qin

Similarity plays a fundamental role in many areas, including data mining, machine learning, statistics and various applied domains.

Clustering Clustering Ensemble

Elephant in the Room: An Evaluation Framework for Assessing Adversarial Examples in NLP

no code implementations22 Jan 2020 Ying Xu, Xu Zhong, Antonio Jose Jimeno Yepes, Jey Han Lau

An adversarial example is an input transformed by small perturbations that machine learning models consistently misclassify.

Sentence

GraphFederator: Federated Visual Analysis for Multi-party Graphs

no code implementations27 Aug 2020 Dongming Han, Wei Chen, Rusheng Pan, Yijing Liu, Jiehui Zhou, Ying Xu, Tianye Zhang, Changjie Fan, Jianrong Tao, Xiaolong, Zhang

This paper presents GraphFederator, a novel approach to construct joint representations of multi-party graphs and supports privacy-preserving visual analysis of graphs.

Human-Computer Interaction Cryptography and Security Graphics

Estimating the Number of Infected Cases in COVID-19 Pandemic

no code implementations24 May 2020 Donghui Yan, Ying Xu, Pei Wang

We propose a structured approach for the estimation of the number of unreported cases, where we distinguish cases that arrive late in the reported numbers and those who had mild or no symptoms and thus were not captured by any medical system at all.

ActionBert: Leveraging User Actions for Semantic Understanding of User Interfaces

no code implementations22 Dec 2020 Zecheng He, Srinivas Sunkara, Xiaoxue Zang, Ying Xu, Lijuan Liu, Nevan Wichers, Gabriel Schubiner, Ruby Lee, Jindong Chen, Blaise Agüera y Arcas

Our methodology is designed to leverage visual, linguistic and domain-specific features in user interaction traces to pre-train generic feature representations of UIs and their components.

Retrieval

Understanding in Artificial Intelligence

no code implementations17 Jan 2021 Stefan Maetschke, David Martinez Iraola, Pieter Barnard, Elaheh ShafieiBavani, Peter Zhong, Ying Xu, Antonio Jimeno Yepes

A question remains of how much understanding is leveraged by these methods and how appropriate are the current benchmarks to measure understanding capabilities.

Natural Language Understanding Question Answering +1

Voltage Inference for and Coordination of Distributed Voltage Controls in Extremely-High DER-Penetration Distribution Networks

no code implementations20 Jan 2021 Ying Xu, Zhihua Qu

The unique problems and phenomena in the distributed voltage control of large-scale power distribution systems with extremely-high DER-penetration are targeted in this paper.

Multimodal Icon Annotation For Mobile Applications

no code implementations9 Jul 2021 Xiaoxue Zang, Ying Xu, Jindong Chen

Annotating user interfaces (UIs) that involves localization and classification of meaningful UI elements on a screen is a critical step for many mobile applications such as screen readers and voice control of devices.

Object object-detection +1

An optimised deep spiking neural network architecture without gradients

no code implementations27 Sep 2021 Yeshwanth Bethi, Ying Xu, Gregory Cohen, Andre van Schaik, Saeed Afshar

Through the use of simple local adaptive selection thresholds at each node, the network rapidly learns to appropriately allocate its neuronal resources at each layer for any given problem without using a real-valued error measure.

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code

no code implementations22 Jun 2022 Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran, Alex Wang, Alexandros Papangelis, Aman Madaan, Angelina McMillan-Major, Anna Shvets, Ashish Upadhyay, Bingsheng Yao, Bryan Wilie, Chandra Bhagavatula, Chaobin You, Craig Thomson, Cristina Garbacea, Dakuo Wang, Daniel Deutsch, Deyi Xiong, Di Jin, Dimitra Gkatzia, Dragomir Radev, Elizabeth Clark, Esin Durmus, Faisal Ladhak, Filip Ginter, Genta Indra Winata, Hendrik Strobelt, Hiroaki Hayashi, Jekaterina Novikova, Jenna Kanerva, Jenny Chim, Jiawei Zhou, Jordan Clive, Joshua Maynez, João Sedoc, Juraj Juraska, Kaustubh Dhole, Khyathi Raghavi Chandu, Laura Perez-Beltrachini, Leonardo F. R. Ribeiro, Lewis Tunstall, Li Zhang, Mahima Pushkarna, Mathias Creutz, Michael White, Mihir Sanjay Kale, Moussa Kamal Eddine, Nico Daheim, Nishant Subramani, Ondrej Dusek, Paul Pu Liang, Pawan Sasanka Ammanamanchi, Qi Zhu, Ratish Puduppully, Reno Kriz, Rifat Shahriyar, Ronald Cardenas, Saad Mahamood, Salomey Osei, Samuel Cahyawijaya, Sanja Štajner, Sebastien Montella, Shailza, Shailza Jolly, Simon Mille, Tahmid Hasan, Tianhao Shen, Tosin Adewumi, Vikas Raunak, Vipul Raheja, Vitaly Nikolaev, Vivian Tsai, Yacine Jernite, Ying Xu, Yisi Sang, Yixin Liu, Yufang Hou

This problem is especially pertinent in natural language generation which requires ever-improving suites of datasets, metrics, and human evaluation to make definitive claims.

Benchmarking Text Generation

Chat-to-Design: AI Assisted Personalized Fashion Design

no code implementations3 Jul 2022 Weiming Zhuang, Chongjie Ye, Ying Xu, Pengzhi Mao, Shuai Zhang

In this demo, we present Chat-to-Design, a new multimodal interaction system for personalized fashion design.

Natural Language Understanding Retrieval

An Optimized Deep Spiking Neural Network Architecture Without Gradients

1 code implementation IEEE Access 2022 Yeshwanth Bethi, Ying Xu, Gregory Cohen, André van Schaik, and Saeed Afshar

Through the use of simple local adaptive selection thresholds at each node, the network rapidly learns to appropriately allocate its neuronal resources at each layer for any given problem without using an error measure.

Phenotype Detection in Real World Data via Online MixEHR Algorithm

no code implementations14 Nov 2022 Ying Xu, Romane Gauriau, Anna Decker, Jacob Oppenheim

Understanding patterns of diagnoses, medications, procedures, and laboratory tests from electronic health records (EHRs) and health insurer claims is important for understanding disease risk and for efficient clinical development, which often require rules-based curation in collaboration with clinicians.

Clinical Knowledge

Event-driven Spectrotemporal Feature Extraction and Classification using a Silicon Cochlea Model

no code implementations14 Dec 2022 Ying Xu, Samalika Perera, Yeshwanth Bethi, Saeed Afshar, André van Schaik

This paper presents a reconfigurable digital implementation of an event-based binaural cochlear system on a Field Programmable Gate Array (FPGA).

FairytaleCQA: Integrating a Commonsense Knowledge Graph into Children's Storybook Narratives

no code implementations16 Nov 2023 Jiaju Chen, Yuxuan Lu, Shao Zhang, Bingsheng Yao, Yuanzhe Dong, Ying Xu, Yunyao Li, Qianwen Wang, Dakuo Wang, Yuling Sun

AI models (including LLM) often rely on narrative question-answering (QA) datasets to provide customized QA functionalities to support downstream children education applications; however, existing datasets only include QA pairs that are grounded within the given storybook content, but children can learn more when teachers refer the storybook content to real-world knowledge (e. g., commonsense knowledge).

Question Answering World Knowledge

Attacks on Node Attributes in Graph Neural Networks

no code implementations19 Feb 2024 Ying Xu, Michael Lanier, Anindya Sarkar, Yevgeniy Vorobeychik

Graphs are commonly used to model complex networks prevalent in modern social media and literacy applications.

Contrastive Learning

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