Search Results for author: Yi Han

Found 15 papers, 2 papers with code

Through the Lens of Core Competency: Survey on Evaluation of Large Language Models

no code implementations15 Aug 2023 Ziyu Zhuang, Qiguang Chen, Longxuan Ma, Mingda Li, Yi Han, Yushan Qian, Haopeng Bai, Zixian Feng, Weinan Zhang, Ting Liu

From pre-trained language model (PLM) to large language model (LLM), the field of natural language processing (NLP) has witnessed steep performance gains and wide practical uses.

Language Modelling Large Language Model

Why Don't You Clean Your Glasses? Perception Attacks with Dynamic Optical Perturbations

no code implementations24 Jul 2023 Yi Han, Matthew Chan, Eric Wengrowski, Zhuohuan Li, Nils Ole Tippenhauer, Mani Srivastava, Saman Zonouz, Luis Garcia

We demonstrate that the dynamic nature of EvilEye enables attackers to adapt adversarial examples across a variety of objects with a significantly higher ASR compared to state-of-the-art physical world attack frameworks.

Deep Graph-Level Clustering Using Pseudo-Label-Guided Mutual Information Maximization Network

no code implementations5 Feb 2023 Jinyu Cai, Yi Han, Wenzhong Guo, Jicong Fan

In this work, we study the problem of partitioning a set of graphs into different groups such that the graphs in the same group are similar while the graphs in different groups are dissimilar.

Clustering Graph Classification +3

Laplacian-based Cluster-Contractive t-SNE for High Dimensional Data Visualization

no code implementations25 Jul 2022 Yan Sun, Yi Han, Jicong Fan

Dimensionality reduction techniques aim at representing high-dimensional data in low-dimensional spaces to extract hidden and useful information or facilitate visual understanding and interpretation of the data.

Data Visualization Dimensionality Reduction +1

Learning to Rank Rationales for Explainable Recommendation

1 code implementation10 Jun 2022 Zhichao Xu, Yi Han, Tao Yang, Anh Tran, Qingyao Ai

Seeing this gap, we propose a model named Semantic-Enhanced Bayesian Personalized Explanation Ranking (SE-BPER) to effectively combine the interaction information and semantic information.

Explainable Recommendation Learning-To-Rank +3

Example-based Real-time Clothing Synthesis for Virtual Agents

no code implementations8 Jan 2021 Nannan Wu, Qianwen Chao, Yanzhen Chen, Weiwei Xu, Chen Liu, Dinesh Manocha, Wenxin Sun, Yi Han, Xinran Yao, Xiaogang Jin

Given a query shape and pose of the virtual agent, we synthesize the resulting clothing deformation by blending the Taylor expansion results of nearby anchoring points.

Graphics

Breaking the Memory Wall for AI Chip with a New Dimension

no code implementations28 Sep 2020 Eugene Tam, Shenfei Jiang, Paul Duan, Shawn Meng, Yue Pang, Cayden Huang, Yi Han, Jacke Xie, Yuanjun Cui, Jinsong Yu, Minggui Lu

Recent advancements in deep learning have led to the widespread adoption of artificial intelligence (AI) in applications such as computer vision and natural language processing.

E-commerce Recommendation with Weighted Expected Utility

no code implementations19 Aug 2020 Zhichao Xu, Yi Han, Yongfeng Zhang, Qingyao Ai

In this paper, we interpret purchase utility as the satisfaction level a consumer gets from a product and propose a recommendation framework using EU to model consumers' behavioral patterns.

Collaborative Filtering Recommendation Systems

Graph Neural Networks with Continual Learning for Fake News Detection from Social Media

2 code implementations7 Jul 2020 Yi Han, Shanika Karunasekera, Christopher Leckie

(2) GNNs trained on a given dataset may perform poorly on new, unseen data, and direct incremental training cannot solve the problem---this issue has not been addressed in the previous work that applies GNNs for fake news detection.

Continual Learning Fact Checking +1

Image Analysis Enhanced Event Detection from Geo-tagged Tweet Streams

no code implementations11 Feb 2020 Yi Han, Shanika Karunasekera, Christopher Leckie

Events detected from social media streams often include early signs of accidents, crimes or disasters.

Event Detection

Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence

no code implementations25 Feb 2019 Yi Han, David Hubczenko, Paul Montague, Olivier De Vel, Tamas Abraham, Benjamin I. P. Rubinstein, Christopher Leckie, Tansu Alpcan, Sarah Erfani

Recent studies have demonstrated that reinforcement learning (RL) agents are susceptible to adversarial manipulation, similar to vulnerabilities previously demonstrated in the supervised learning setting.

reinforcement-learning Reinforcement Learning (RL)

Reinforcement Learning for Autonomous Defence in Software-Defined Networking

no code implementations17 Aug 2018 Yi Han, Benjamin I. P. Rubinstein, Tamas Abraham, Tansu Alpcan, Olivier De Vel, Sarah Erfani, David Hubczenko, Christopher Leckie, Paul Montague

Despite the successful application of machine learning (ML) in a wide range of domains, adaptability---the very property that makes machine learning desirable---can be exploited by adversaries to contaminate training and evade classification.

BIG-bench Machine Learning General Classification +2

Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks

no code implementations6 Apr 2017 Yi Han, Benjamin I. P. Rubinstein

Despite the wide use of machine learning in adversarial settings including computer security, recent studies have demonstrated vulnerabilities to evasion attacks---carefully crafted adversarial samples that closely resemble legitimate instances, but cause misclassification.

Computer Security

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