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Artificial Intelligence and Robotics
Research Collection School Of Computing and Information Systems
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Articles 91 - 99 of 99
Full-Text Articles in Physical Sciences and Mathematics
Who Am I?: Towards Social Self-Awareness For Intelligent Agents, Budhitama Subagdja, Han Yi Tay, Ah-Hwee Tan
Who Am I?: Towards Social Self-Awareness For Intelligent Agents, Budhitama Subagdja, Han Yi Tay, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Most of today’s AI technologies are geared towards mastering specific tasks performance through learning from a huge volume of data. However, less attention has still been given to make the AI understand its own purposes or be responsible socially. In this paper, a new model of agent is presented with the capacity to represent itself as a distinct individual with identity, a mind of its own, unique experiences, and social lives. In this way, the agent can interact with its surroundings and other agents seamlessly and meaningfully. A practical framework for developing an agent architecture with this model of self …
Fakespotter: A Simple Yet Robust Baseline For Spotting Ai-Synthesized Fake Faces, Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, Yang Liu
Fakespotter: A Simple Yet Robust Baseline For Spotting Ai-Synthesized Fake Faces, Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, Yang Liu
Research Collection School Of Computing and Information Systems
In recent years, generative adversarial networks (GANs) and its variants have achieved unprecedented success in image synthesis. They are widely adopted in synthesizing facial images which brings potential security concerns to humans as the fakes spread and fuel the misinformation. However, robust detectors of these AI-synthesized fake faces are still in their infancy and are not ready to fully tackle this emerging challenge. In this work, we propose a novel approach, named FakeSpotter, based on monitoring neuron behaviors to spot AIsynthesized fake faces. The studies on neuron coverage and interactions have successfully shown that they can be served as testing …
The Value Of Humanization In Customer Service, Yang Gao, Huaxia Rui, Shujing Sun
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 …
Zone Path Construction (Zac) Based Approaches For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Zone Path Construction (Zac) Based Approaches For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Real-time ridesharing systems such as UberPool, Lyft Line and GrabShare have become hugely popular as they reduce the costs for customers, improve per trip revenue for drivers and reduce traffic on the roads by grouping customers with similar itineraries. The key challenge in these systems is to group the “right” requests to travel together in the “right” available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. This challenge has been addressed in existing work by: (i) generating as many relevant feasible combinations of requests (with respect to the available delay for customers) as …
What Makes A Popular Academic Ai Repository?, Yuanrui Fan, Xin Xia, David Lo, Ahmed E. Hassan, Shanping Li
What Makes A Popular Academic Ai Repository?, Yuanrui Fan, Xin Xia, David Lo, Ahmed E. Hassan, Shanping Li
Research Collection School Of Computing and Information Systems
Many AI researchers are publishing code, data and other resources that accompany their papers in GitHub repositories. In this paper, we refer to these repositories as academic AI repositories. Our preliminary study shows that highly cited papers are more likely to have popular academic AI repositories (and vice versa). Hence, in this study, we perform an empirical study on academic AI repositories to highlight good software engineering practices of popular academic AI repositories for AI researchers. We collect 1,149 academic AI repositories, in which we label the top 20% repositories that have the most number of stars as popular, and …
A Continual Deepfake Detection Benchmark: Dataset, Methods, And Essentials, Chuqiao Li, Zhiwu Huang, Danda Pani Paudel, Yabin Wang, Mohamad Shahbazi, Xiaopeng Hong, Van Gool Luc
A Continual Deepfake Detection Benchmark: Dataset, Methods, And Essentials, Chuqiao Li, Zhiwu Huang, Danda Pani Paudel, Yabin Wang, Mohamad Shahbazi, Xiaopeng Hong, Van Gool Luc
Research Collection School Of Computing and Information Systems
There have been emerging a number of benchmarks and techniques for the detection of deepfakes. However, very few works study the detection of incrementally appearing deepfakes in the real-world scenarios. To simulate the wild scenes, this paper suggests a continual deepfake detection benchmark (CDDB) over a new collection of deepfakes from both known and unknown generative models. The suggested CDDB designs multiple evaluations on the detection over easy, hard, and long sequence of deepfake tasks, with a set of appropriate measures. In addition, we exploit multiple approaches to adapt multiclass incremental learning methods, commonly used in the continual visual recognition, …
3d Dental Biometrics: Automatic Pose-Invariant Dental Arch Extraction And Matching, Xin Zhong, Zhiyuan Zhang
3d Dental Biometrics: Automatic Pose-Invariant Dental Arch Extraction And Matching, Xin Zhong, Zhiyuan Zhang
Research Collection School Of Computing and Information Systems
A novel automatic pose-invariant dental arch extraction and matching framework is developed for 3D dental identification using laser-scanned dental plasters. In our previous attempt [1-5], 3D point-based algorithms have been developed and they have shown a few advantages over existing 2D dental identifications. This study is a continuous effort in developing arch-based algorithms to extract and match dental arch feature in an automatic and pose-invariant way. As best as we know, this is the first attempt at automatic dental arch extraction and matching for 3D dental identification. A Radial Ray Algorithm (RRA) is proposed by projecting dental arch shape from …
Partial Adversarial Behavior Deception In Security Games, Thanh H. Nguyen, Arunesh Sinha, He He
Partial Adversarial Behavior Deception In Security Games, Thanh H. Nguyen, Arunesh Sinha, He He
Research Collection School Of Computing and Information Systems
Learning attacker behavior is an important research topic in security games as security agencies are often uncertain about attackers’ decision making. Previous work has focused on developing various behavioral models of attackers based on historical attack data. However, a clever attacker can manipulate its attacks to fail such attack-driven learning, leading to ineffective defense strategies. We study attacker behavior deception with three main contributions. First, we propose a new model, named partial behavior deception model, in which there is a deceptive attacker (among multiple attackers) who controls a portion of attacks. Our model captures real-world security scenarios such as wildlife …
Scalable Online Vetting Of Android Apps For Measuring Declared Sdk Versions And Their Consistency With Api Calls, Daoyuan Wu, Debin Gao, David Lo
Scalable Online Vetting Of Android Apps For Measuring Declared Sdk Versions And Their Consistency With Api Calls, Daoyuan Wu, Debin Gao, David Lo
Research Collection School Of Computing and Information Systems
Android has been the most popular smartphone system with multiple platform versions active in the market. To manage the application’s compatibility with one or more platform versions, Android allows apps to declare the supported platform SDK versions in their manifest files. In this paper, we conduct a systematic study of this modern software mechanism. Our objective is to measure the current practice of declared SDK versions (which we term as DSDK versions afterwards) in real apps, and the (in)consistency between DSDK versions and their host apps’ API calls. To successfully analyze a modern dataset of 22,687 popular apps (with an …