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Cross-Topic Rumor Detection Using Topic-Mixtures, Weijieying Ren, Jing Jiang, Ling Min Serena Khoo, Hai Leong Chieu Apr 2021

Cross-Topic Rumor Detection Using Topic-Mixtures, Weijieying Ren, Jing Jiang, Ling Min Serena Khoo, Hai Leong Chieu

Research Collection School Of Computing and Information Systems

There has been much interest in rumor detection using deep learning models in recent years. A well-known limitation of deep learning models is that they tend to learn superficial patterns, which restricts their generalization ability. We find that this is also true for cross-topic rumor detection. In this paper, we propose a method inspired by the “mixture of experts” paradigm. We assume that the prediction of the rumor class label given an instance is dependent on the topic distribution of the instance. After deriving a vector representation for each topic, given an instance, we derive a “topic mixture” vector for …

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Multi-Domain Dialogue State Tracking With Recursive Inference, Lizi Liao, Tongyao Zhu, Le Hong Long, Tat-Seng Chua Apr 2021

Multi-Domain Dialogue State Tracking With Recursive Inference, Lizi Liao, Tongyao Zhu, Le Hong Long, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Multi-domain dialogue state tracking (DST) is a critical component for monitoring user goals during the course of an interaction. Existing approaches have relied on dialogue history indiscriminately or updated on the most recent turns incrementally. However, in spite of modeling it based on fixed ontology or open vocabulary, the former setting violates the interactive and progressing nature of dialogue, while the later easily gets affected by the error accumulation conundrum. Here, we propose a Recursive Inference mechanism (ReInf) to resolve DST in multi-domain scenarios that call for more robust and accurate tracking capability. Specifically, our agent reversely reviews the dialogue …

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Enhancing Cultural Intelligence And Digital Literacy In Accounting Education: Insights From A University’S Global Student Consulting Programme, Clarence Goh, Yuanto Kusnadi, Gary Pan, Poh Sun Seow Apr 2021

Enhancing Cultural Intelligence And Digital Literacy In Accounting Education: Insights From A University’S Global Student Consulting Programme, Clarence Goh, Yuanto Kusnadi, Gary Pan, Poh Sun Seow

Research Collection School Of Accountancy

Recent literature has advocated for the use of project based learning to engage students in active learning. This study examines how students’ learning of cultural intelligence and digital literacy are enhanced through an overseas project-based learning (PBL) programme at a Singapore University (UNIS), called the UNIS-XO pedagogy. Specifically, this study provides a framework through which students, faculty members, and industry partner can collaborate through consulting programs with the aim to provide feasible recommendations to the clients. Our findings suggest that an experiential PBL with an overseas client is an important learning experience through which students can strengthen their digital literacy …

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Teaching In The Right Context: Textbook Supply Program, Language, And Vocabulary Ability In Vietnam, Tomoki Fujii, Maki Nakajima, Sijia Xu Apr 2021

Teaching In The Right Context: Textbook Supply Program, Language, And Vocabulary Ability In Vietnam, Tomoki Fujii, Maki Nakajima, Sijia Xu

Research Collection School Of Economics

While past two decades have witnessed a remarkable educational progress in Vietnam, ethnic minority children consistently lagged behind ethnic majority children in academic performance. The government of Vietnam has stepped up efforts to assist ethnic minority students in their learning by lowering the linguistic and cultural barriers they face. Among such efforts is the textbook supply program, and we examine its impact on the learning of children proxied by vocabulary test. We apply difference-in-differences estimation to four rounds of the Young Lives data between 2006 and 2015 in order to investigate how the textbook supply program narrowed the gap between …

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Tour: Dynamic Topic And Sentiment Analysis Of User Reviews For Assisting App Release, Tianyi Yang, Cuiyun Gao, Jingya Zang, David Lo, Michael R. Lyu Apr 2021

Tour: Dynamic Topic And Sentiment Analysis Of User Reviews For Assisting App Release, Tianyi Yang, Cuiyun Gao, Jingya Zang, David Lo, Michael R. Lyu

Research Collection School Of Computing and Information Systems

App reviews deliver user opinions and emerging issues (e.g., new bugs) about the app releases. Due to the dynamic nature of app reviews, topics and sentiment of the reviews would change along with app release versions. Although several studies have focused on summarizing user opinions by analyzing user sentiment towards app features, no practical tool is released. The large quantity of reviews and noise words also necessitates an automated tool for monitoring user reviews. In this paper, we introduce TOUR for dynamic TOpic and sentiment analysis of User Reviews. TOUR is able to (i) detect and summarize emerging app issues …

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Escape From An Echo Chamber, Kuan-Chieh Lo, Shih-Chieh Dai, Aiping Xiong, Jing Jiang, Lun-Wei Ku Apr 2021

Escape From An Echo Chamber, Kuan-Chieh Lo, Shih-Chieh Dai, Aiping Xiong, Jing Jiang, Lun-Wei Ku

Research Collection School Of Computing and Information Systems

An echo chamber effect refers to the phenomena that online users revealed selective exposure and ideological segregation on political issues. Prior studies indicate the connection between the spread of misinformation and online echo chambers. In this paper, to help users escape from an echo chamber, we propose a novel news-analysis platform that provides a panoramic view of stances towards a particular event from different news media sources. Moreover, to help users better recognize the stances of news sources which published these news articles, we adopt a news stance classification model to categorize their stances into “agree”, “disagree”, “discuss”, or “unrelated” …

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Introduction To The Special Issue On “Grassroots And Inclusive Innovations: Conceptualizing Synergies And Complementarities”, Wee Liang Tan, Partha Gangopadhyay, Oscar Hauptman Mar 2021

Introduction To The Special Issue On “Grassroots And Inclusive Innovations: Conceptualizing Synergies And Complementarities”, Wee Liang Tan, Partha Gangopadhyay, Oscar Hauptman

Research Collection Lee Kong Chian School Of Business

The paper provided a review of the state of the field of grassroots and inclusive innovations, suggested and proposed ways forward for research. It also provided a summary of the articles in the special issue and discussed their contributions. With the extant literature, and the modest contribution of the special issue, the paper postulates that grassroots innovation and inclusive innovation activities are complementary. One the one hand, the inclusive innovations actors and processes facilitate and accelerate grassroots innovation. On the other hand, the knowledge of local context and culture enables effective diffusion of external ideas. The paper also highlights the …

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Introduction To The Special Issue On “Grassroots And Inclusive Innovations: Conceptualizing Synergies And Complementarities”, Wee Liang Tan, Partha Gangopadhyay, Oscar Hauptman Mar 2021

Introduction To The Special Issue On “Grassroots And Inclusive Innovations: Conceptualizing Synergies And Complementarities”, Wee Liang Tan, Partha Gangopadhyay, Oscar Hauptman

Research Collection Lee Kong Chian School Of Business

This special issue was initiated in 2016 by the three co-editors with a “Call for Papers” (Gangopadhyay et al., 2016). After significant delays starting with co-editors’ health and other personal issues, and ending with the COVID-19 Pandemic, the task of finalizing the special issue is reaching conclusion and it is time to take stock of the intellectual content. The objective of this introduction is to enable the audience to make easier sense when perusing the papers selected in a broader context, guided by conceptual framing.

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Populist Supporters On Reddit: A Comparison Of Content And Behavioral Patterns Within Publics Of Supporters Of Donald Trump And Hillary Clinton, Andreas Jungherr, Oliver Posegga, Jisun An Mar 2021

Populist Supporters On Reddit: A Comparison Of Content And Behavioral Patterns Within Publics Of Supporters Of Donald Trump And Hillary Clinton, Andreas Jungherr, Oliver Posegga, Jisun An

Research Collection School Of Computing and Information Systems

The international rise of populism has been attributed, in part, to digital media. These media allow the backers of populists to share and distribute information independent of traditional media organizations or elites and offer communication spaces in which they can support each other and strengthen communal ties irrespective of their societal standing. Can we identify these functions in distinct usage patterns of digital media by supporters of populists? This could find expression through posting content that comports with the central tenets of populist ideology, higher activity levels, use of distinct vocabularies, and heightened levels of community building. We investigate differences …

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Selling A Resume And Buying A Job: Stratification Of Gender And Occupation By States And Brokers In International Migration From Indonesia, Andy Scott Chang Mar 2021

Selling A Resume And Buying A Job: Stratification Of Gender And Occupation By States And Brokers In International Migration From Indonesia, Andy Scott Chang

Research Collection School of Social Sciences

This study examines how state and commercial actors construct gender, occupation, and nationality hierarchies in guest worker programs by comparing the migratory procedures for female domestic workers and male industrial operators from Indonesia. Based on 19 months of multi-sited ethnography and 86 interviews in Indonesia, Taiwan, and Singapore, I introduce the notion of multilateralism to theorize the stratification of global migration processes. In multilateral labor markets, governments, brokers, employers, and migrants in multiple countries contend for labor and employment. The homecare market is governed under the rubric of “selling a resume,” whereby Indonesian regulators and labor suppliers pass on recruitment …

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Decision-Guided Weighted Automata Extraction From Recurrent Neural Networks, Xiyue Zhang, Xiaoning Du, Xiaofei Xie, Lei Ma, Yang Liu, Meng Sun Feb 2021

Decision-Guided Weighted Automata Extraction From Recurrent Neural Networks, Xiyue Zhang, Xiaoning Du, Xiaofei Xie, Lei Ma, Yang Liu, Meng Sun

Research Collection School Of Computing and Information Systems

Recurrent Neural Networks (RNNs) have demonstrated their effectiveness in learning and processing sequential data (e.g., speech and natural language). However, due to the black-box nature of neural networks, understanding the decision logic of RNNs is quite challenging. Some recent progress has been made to approximate the behavior of an RNN by weighted automata. They provide better interpretability, but still suffer from poor scalability. In this paper, we propose a novel approach to extracting weighted automata with the guidance of a target RNN’s decision and context information. In particular, we identify the patterns of RNN’s step-wise predictive decisions to instruct the …

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Evidence Aware Neural Pornographic Text Identification For Child Protection, Kaisong Song, Yangyang Kang, Wei Gao, Zhe Gao, Changlong Sun, Xiaozhong Liu Feb 2021

Evidence Aware Neural Pornographic Text Identification For Child Protection, Kaisong Song, Yangyang Kang, Wei Gao, Zhe Gao, Changlong Sun, Xiaozhong Liu

Research Collection School Of Computing and Information Systems

Identifying pornographic text online is practically useful to protect children from access to such adult content. However, some authors may intentionally avoid using sensitive words in their pornographic texts to take advantage of the lack of human audits. Without prior knowledge guidance, real semantics of such pornographic text is difficult to understand by existing methods due to its high context-sensitivity and heavy usage of figurative language, which brings huge challenges to the porn detection systems used in social media platforms. In this paper, we approach to the problem as a document-level porn identification task by locating and integrating sentence-level evidence …

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Transaction Cost Theory: Past Progress, Current Challenges, And Suggestions For The Future, Ilya Cuypers, Jean-Francois Hennart, Brian S. Silverman, Gokhan Ertug Feb 2021

Transaction Cost Theory: Past Progress, Current Challenges, And Suggestions For The Future, Ilya Cuypers, Jean-Francois Hennart, Brian S. Silverman, Gokhan Ertug

Research Collection Lee Kong Chian School Of Business

Transaction cost theory (TCT) has been fruitfully applied to a wide range of organizational phenomena, as reflected in a vast and evolving body of research. However, in part due to the theory’s broad success, important advances in some fields do not diffuse to other fields. In this essay, we lay out a path toward a pluralistic view of TCT that incorporates insights from multiple fields, primarily strategy and international business. In so doing, we critically assess the assumptions, key constructs, and evolving theoretical logic of TCT. We then propose an agenda for future research, highlighting opportunities for scholars to (1) …

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Mind Your Language: The Effects Of Linguistic Ostracism On Interpersonal Work Behaviors, John Fiset, Devasheesh P. Bhave Feb 2021

Mind Your Language: The Effects Of Linguistic Ostracism On Interpersonal Work Behaviors, John Fiset, Devasheesh P. Bhave

Research Collection Lee Kong Chian School Of Business

Business and demographic trends are conflating to bring language issues at work to the forefront. Although language has an inherent capacity for creating interpersonal bonds, it can also serve as a means of exclusion. The construct of linguistic ostracism encapsulates this phenomenon. Drawing on ethnolinguistic identity theory, we identify how linguistic ostracism influences two interpersonal work behaviors: interpersonal citizenship and interpersonal deviance. We conduct a set of studies that uses multisource data, data across time, and data from three countries. Our results reveal that linguistic ostracism was associated with the enactment of lower interpersonal citizenship behaviors and higher interpersonal deviance …

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Treecaps: Tree-Based Capsule Networks For Source Code Processing, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang Feb 2021

Treecaps: Tree-Based Capsule Networks For Source Code Processing, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Recently program learning techniques have been proposed to process source code based on syntactical structures (e.g., Abstract Syntax Trees) and/or semantic information (e.g., Dependency Graphs). While graphs may be better at capturing various viewpoints of code semantics than trees, constructing graph inputs from code need static code semantic analysis that may not be accurate and introduces noise during learning. On the other hand, syntax trees are precisely defined according to the language grammar and easier to construct and process than graphs. We propose a new tree-based learning technique, named TreeCaps, by fusing capsule networks with tree-based convolutional neural networks, to …

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Culturally Diverse Expert Teams Have Yet To Bring Comprehensive Linguistic Diversity To Intergovernmental Ecosystem Assessments, Abigail J. Lynch, Fernández-Llamazares Álvaro, Ignacio Palomo, Pedro Jaureguiberry, Amano Tatsuya, Zeenatul Basher, Michelle Lim, Tuyeni Heita Mwampamba, Aibek Samakov, Odirilwe Selomane, Michelle Mei Ling Lim Feb 2021

Culturally Diverse Expert Teams Have Yet To Bring Comprehensive Linguistic Diversity To Intergovernmental Ecosystem Assessments, Abigail J. Lynch, Fernández-Llamazares Álvaro, Ignacio Palomo, Pedro Jaureguiberry, Amano Tatsuya, Zeenatul Basher, Michelle Lim, Tuyeni Heita Mwampamba, Aibek Samakov, Odirilwe Selomane, Michelle Mei Ling Lim

Research Collection Yong Pung How School Of Law

Multicultural representation is a stated goal of many global scientific assessment processes. These processes aim to mobilize a broader, more diverse knowledge base and increase legitimacy and inclusiveness of these assessment processes. Often, enhancing cultural diversity is encouraged through involvement of diverse expert teams and sources of knowledge in different languages. In this article, we examine linguistic diversity, as one representation of cultural diversity, in the eight published assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). Our results show that the IPBES assessment outputs are disproportionately filtered through English-language literature and authors from Anglophone countries. To …

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Chronic Customers Or Increased Awareness? The Dynamics Of Social Media Customer Service, Shujing Sun, Yang Gao, Huaxia Rui Jan 2021

Chronic Customers Or Increased Awareness? The Dynamics Of Social Media Customer Service, Shujing Sun, Yang Gao, Huaxia Rui

Research Collection School Of Computing and Information Systems

Despite that social media has become a promising alternative to traditional call centers, managers hesitate to fully harness its power because they worry that active service intervention may encourage excessive use of the channel by disgruntled customers. This paper sheds light on such a concern by examining the dynamics between brand-level customer complaints and service interventions on social media. Using details of customer-brand interactions of 40 airlines on Twitter, we find that more service interventions indeed cause more customer complaints, accounting for the online customer population and service quality. However, the increased complaints are primarily driven by the awareness enhancement …

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Rapid Transition Of A Technical Course From Face-To-Face To Online, Swapna Gottipatti, Venky Shankaraman Jan 2021

Rapid Transition Of A Technical Course From Face-To-Face To Online, Swapna Gottipatti, Venky Shankaraman

Research Collection School Of Computing and Information Systems

Just like most universities around the world, the senior management at Singapore Management University decided to move all courses to a virtual, online, synchronous mode, giving instructors a very short notice period—one week—to make this transition. In this paper, we describe the challenges, practical solutions adopted, and the lessons learnt in rapidly transitioning a face-to-face Master’s degree course in Text Analytics and Applications into a virtual, online, course format that could deliver a quality learning experience.

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'Fraught' Chineseness: 'Chinese Christians' In The Vancouver Sun, Justin Kh Tse Jan 2021

'Fraught' Chineseness: 'Chinese Christians' In The Vancouver Sun, Justin Kh Tse

Research Collection School of Social Sciences

This chapter explores the ways in which Douglas Todd, a journalist for the Vancouver Sun, has covered stories about Chinese churches in Vancouver, BC, for over three decades. It shows how Todd has focused on Chinese Christians as a way to offer a particular perspective on religion and cultural diversity in Vancouver, and as a window into their relationship with the civil society. Ultimately, this chapter highlights the ways in which Todd essentializes “Chineseness” and reinforces a problematic public narrative of homogeneity among Vancouver’s Chinese Christians.

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The Value Of Humanization In Customer Service, Yang Gao, Huaxia Rui, Shujing Sun Jan 2021

The Value Of Humanization In Customer Service, Yang Gao, Huaxia Rui, Shujing Sun

Research Collection School Of Computing and Information Systems

As algorithm-based agents become increasingly capable of handling customer service queries, customers are often uncertain whether they are served by humans or algorithms, and managers are left to question the value of human agents once the technology matures. The current paper studies this question by quantifying the impact of customers' enhanced perception of being served by human agents on customer service interactions. Our identification strategy hinges on the abrupt implementation by Southwest Airlines of a signature policy, which requires the inclusion of an agent's first name in responses on Twitter, thereby making the agent more humanized in the eyes of …

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Spandeck: A Relational View Of The Duty Of Care, Kian Peng Soh Jan 2021

Spandeck: A Relational View Of The Duty Of Care, Kian Peng Soh

Research Collection Yong Pung How School Of Law

The use of a general framework in the determination of a duty of care has seemingly fallen out of favour following the UK Supreme Court’s decision in Robinson. Relying on the example of the Spandeck framework in Singaporean jurisprudence, this piece presents the argument that such frameworks, being consistent with a relational conception of tort law, can provide a useful means of determining whether a duty of care exists. In so doing, this piece addresses some criticisms of the relational view and re-emphasises the important role the duty of care plays in the tort of negligence.

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Hategan: Adversarial Generative-Based Data Augmentation For Hate Speech Detection, Rui Cao, Roy Ka-Wei Lee Dec 2020

Hategan: Adversarial Generative-Based Data Augmentation For Hate Speech Detection, Rui Cao, Roy Ka-Wei Lee

SCIS Student Publications

Academia and industry have developed machine learning and natural language processing models to detect online hate speech automatically. However, most of these existing methods adopt a supervised approach that heavily depends on labeled datasets for training. This results in the methods’ poor detection performance of the hate speech class as the training datasets are highly imbalanced. In this paper, we propose HateGAN, a deep generative reinforcement learning model, which addresses the challenge of imbalance class by augmenting the dataset with hateful tweets. We conduct extensive experiments to augment two commonly-used hate speech detection datasets with the HateGAN generated tweets. Our …

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Jointly Optimizing Sensing Pipelines For Multimodal Mixed Reality Interaction, Ramesh Darshana Rathnayake Kanatta Gamage, Ashen De Silva, Dasun Puwakdandawa, Lakmal Meegahapola, Archan Misra, Indika Perera Dec 2020

Jointly Optimizing Sensing Pipelines For Multimodal Mixed Reality Interaction, Ramesh Darshana Rathnayake Kanatta Gamage, Ashen De Silva, Dasun Puwakdandawa, Lakmal Meegahapola, Archan Misra, Indika Perera

Research Collection School Of Computing and Information Systems

Natural human interactions for Mixed Reality Applications are overwhelmingly multimodal: humans communicate intent and instructions via a combination of visual, aural and gestural cues. However, supporting low-latency and accurate comprehension of such multimodal instructions (MMI), on resource-constrained wearable devices, remains an open challenge, especially as the state-of-the-art comprehension techniques for each individual modality increasingly utilize complex Deep Neural Network models. We demonstrate the possibility of overcoming the core limitation of latency–vs.–accuracy tradeoff by exploiting cross-modal dependencies–i.e., by compensating for the inferior performance of one model with an increased accuracy of more complex model of a different modality. We present a …

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Deep Multi-Task Learning For Depression Detection And Prediction In Longitudinal Data, Guansong Pang, Ngoc Thien Anh Pham, Emma Baker, Rebecca Bentley, Anton Van Den Hengel Dec 2020

Deep Multi-Task Learning For Depression Detection And Prediction In Longitudinal Data, Guansong Pang, Ngoc Thien Anh Pham, Emma Baker, Rebecca Bentley, Anton Van Den Hengel

Research Collection School Of Computing and Information Systems

Depression is among the most prevalent mental disorders, affecting millions of people of all ages globally. Machine learning techniques have shown effective in enabling automated detection and prediction of depression for early intervention and treatment. However, they are challenged by the relative scarcity of instances of depression in the data. In this work we introduce a novel deep multi-task recurrent neural network to tackle this challenge, in which depression classification is jointly optimized with two auxiliary tasks, namely one-class metric learning and anomaly ranking. The auxiliary tasks introduce an inductive bias that improves the classification model's generalizability on small depression …

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Generating Concept Based Api Element Comparison Using A Knowledge Graph, Yang Liu, Mingwei Liu, Xin Peng, Christoph Treude, Zhenchang Xing, Xiaoxin Zhang Dec 2020

Generating Concept Based Api Element Comparison Using A Knowledge Graph, Yang Liu, Mingwei Liu, Xin Peng, Christoph Treude, Zhenchang Xing, Xiaoxin Zhang

Research Collection School Of Computing and Information Systems

Recommender systems are a valuable tool for software engineers. For example, they can provide developers with a ranked list of files likely to contain a bug, or multiple auto-complete suggestions for a given method stub. However, the way these recommender systems interact with developers is often rudimentary—a long list of recommendations only ranked by the model’s confidence. In this vision paper, we lay out our research agenda for re-imagining how recommender systems for software engineering communicate their insights to developers. When issuing recommendations, our aim is to recommend diverse rather than redundant solutions and present them in ways that highlight …

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Improving Gan Training With Probability Ratio Clipping And Sample Reweighting, Yue Wu, Pan Zhou, Andrew Wilson Gordon, Eric Xing, Zhiting Hu Dec 2020

Improving Gan Training With Probability Ratio Clipping And Sample Reweighting, Yue Wu, Pan Zhou, Andrew Wilson Gordon, Eric Xing, Zhiting Hu

Research Collection School Of Computing and Information Systems

Despite success on a wide range of problems related to vision, generative adversarial networks (GANs) often suffer from inferior performance due to unstable training, especially for text generation. To solve this issue, we propose a new variational GAN training framework which enjoys superior training stability. Our approach is inspired by a connection of GANs and reinforcement learning under a variational perspective. The connection leads to (1) probability ratio clipping that regularizes generator training to prevent excessively large updates, and (2) a sample re-weighting mechanism that improves discriminator training by downplaying bad-quality fake samples. Moreover, our variational GAN framework can provably …

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Debunking Rumors On Twitter With Tree Transformer, Jing Ma, Wei Gao Dec 2020

Debunking Rumors On Twitter With Tree Transformer, Jing Ma, Wei Gao

Research Collection School Of Computing and Information Systems

Rumors are manufactured with no respect for accuracy, but can circulate quickly and widely by "word-of-post" through social media conversations. Conversation tree encodes important information indicative of the credibility of rumor. Existing conversation-based techniques for rumor detection either just strictly follow tree edges or treat all the posts fully-connected during feature learning. In this paper, we propose a novel detection model based on tree transformer to better utilize user interactions in the dialogue where post-level self-attention plays the key role for aggregating the intra-/inter-subtree stances. Experimental results on the TWITTER and PHEME datasets show that the proposed approach consistently improves …

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Semantic And Network Evolution In Crowdsourced Idea Refinement, Zhi Wei Vincent Mack, Qian Tang Dec 2020

Semantic And Network Evolution In Crowdsourced Idea Refinement, Zhi Wei Vincent Mack, Qian Tang

Research Collection School Of Computing and Information Systems

Successful ideation is a cornerstone of development. Advancements in information technology have allowed firms to harness collective intelligence through crowdsourcing ideation. New ideas often undergo iterative development and evaluation during a refinement phase, and only high-quality ideas get accepted for implementation. Therefore, our paper studies how idea refinement influences idea quality from both the content semantics and network structure perspectives, in the context of the online ideation community of TVTropes. For the content revisions of the idea, we examine the influence of semantic stability and convergence. For the network evolution of the idea, we investigate the impacts of refined network …

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A Hybrid Approach For Detecting Prerequisite Relations In Multi-Modal Food Recipes, Liangming Pan, Jingjing Chen, Shaoteng Liu, Chong-Wah Ngo, Min-Yen Kan, Tat-Seng Chua Dec 2020

A Hybrid Approach For Detecting Prerequisite Relations In Multi-Modal Food Recipes, Liangming Pan, Jingjing Chen, Shaoteng Liu, Chong-Wah Ngo, Min-Yen Kan, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Modeling the structure of culinary recipes is the core of recipe representation learning. Current approaches mostly focus on extracting the workflow graph from recipes based on text descriptions. Process images, which constitute an important part of cooking recipes, has rarely been investigated in recipe structure modeling. We study this recipe structure problem from a multi-modal learning perspective, by proposing a prerequisite tree to represent recipes with cooking images at a step-level granularity. We propose a simple-yet-effective two-stage framework to automatically construct the prerequisite tree for a recipe by (1) utilizing a trained classifier to detect pairwise prerequisite relations that fuses …

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Interventional Few-Shot Learning, Zhongqi Yue, Zhang Hanwang, Qianru Sun, Xian-Sheng Hua Dec 2020

Interventional Few-Shot Learning, Zhongqi Yue, Zhang Hanwang, Qianru Sun, Xian-Sheng Hua

Research Collection School Of Computing and Information Systems

We uncover an ever-overlooked deficiency in the prevailing Few-Shot Learning (FSL) methods: the pre-trained knowledge is indeed a confounder that limits the performance. This finding is rooted from our causal assumption: a Structural Causal Model (SCM) for the causalities among the pre-trained knowledge, sample features, and labels. Thanks to it, we propose a novel FSL paradigm: Interventional Few-Shot Learning (IFSL). Specifically, we develop three effective IFSL algorithmic implementations based on the backdoor adjustment, which is essentially a causal intervention towards the SCM of many-shot learning: the upper-bound of FSL in a causal view. It is worth noting that the contribution …

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