Hooi, Bryan

91 publications

ICML 2025 Adapting Precomputed Features for Efficient Graph Condensation Yuan Li, Jun Hu, Zemin Liu, Bryan Hooi, Jia Chen, Bingsheng He

ICLR 2025 CHiP: Cross-Modal Hierarchical Direct Preference Optimization for Multimodal LLMs Jinlan Fu, Huangfushenzhen, Hao Fei, Xiaoyu Shen, Bryan Hooi, Xipeng Qiu, See-Kiong Ng

ICLRW 2025 Campolina: A Deep Neural Framework for Accurate Segmentation of Nanopore Signals Sara Bakić, Kresimir Friganovic, Bryan Hooi, Mile Sikic

ICLRW 2025 Can Knowledge Graphs Make Large Language Models More Trustworthy? an Empirical Study over Open-Ended Question Answering Yuan Sui, Yufei He, Zifeng Ding, Bryan Hooi

ICLRW 2025 Chain-of-Timeline: Enhancing LLM Zero-Shot Temporal Reasoning with SQL-Style Timeline Formalization Jiaying Wu, Bryan Hooi

NeurIPS 2025 ConfTuner: Training Large Language Models to Express Their Confidence Verbally Yibo Li, Miao Xiong, Jiaying Wu, Bryan Hooi

CVPR 2025 Exploring Visual Vulnerabilities via Multi-Loss Adversarial Search for Jailbreaking Vision-Language Models Shuyang Hao, Bryan Hooi, Jun Liu, Kai-Wei Chang, Zi Huang, Yujun Cai

ICLRW 2025 FiDeLiS: Faithful Reasoning in Large Language Models for Knowledge Graph Question Answering Yuan Sui, Yufei He, Nian Liu, Xiaoxin He, Kun Wang, Bryan Hooi

ICML 2025 FlipAttack: Jailbreak LLMs via Flipping Yue Liu, Xiaoxin He, Miao Xiong, Jinlan Fu, Shumin Deng, Yingwei Ma, Jiaheng Zhang, Bryan Hooi

ICLRW 2025 FlipAttack: Jailbreak LLMs via Flipping Yue Liu, Xiaoxin He, Miao Xiong, Jinlan Fu, Shumin Deng, Yingwei Ma, Jiaheng Zhang, Bryan Hooi

NeurIPS 2025 GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-Tuning Haonan Yuan, Qingyun Sun, Junhua Shi, Xingcheng Fu, Bryan Hooi, Jianxin Li, Philip S. Yu

ICLRW 2025 Geneshift: Impact of Different Scenario Shift on Jailbreaking LLM Tianyi Wu, Zhiwei Xue, Yue Liu, Jiaheng Zhang, Bryan Hooi, See-Kiong Ng

NeurIPS 2025 GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning Yue Liu, Shengfang Zhai, Mingzhe Du, Yulin Chen, Tri Cao, Hongcheng Gao, Cheng Wang, Xinfeng Li, Kun Wang, Junfeng Fang, Jiaheng Zhang, Bryan Hooi

ICLRW 2025 GuardReasoner: Towards Reasoning-Based LLM Safeguards Yue Liu, Hongcheng Gao, Shengfang Zhai, Jun Xia, Tianyi Wu, Zhiwei Xue, Yulin Chen, Kenji Kawaguchi, Jiaheng Zhang, Bryan Hooi

ICML 2025 How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees Haonan Yuan, Qingyun Sun, Junhua Shi, Xingcheng Fu, Bryan Hooi, Jianxin Li, Philip S. Yu

NeurIPS 2025 MLR-Bench: Evaluating AI Agents on Open-Ended Machine Learning Research Hui Chen, Miao Xiong, Yujie Lu, Wei Han, Ailin Deng, Yufei He, Jiaying Wu, Yibo Li, Yue Liu, Bryan Hooi

AAAI 2025 Modality-Independent Graph Neural Networks with Global Transformers for Multimodal Recommendation Jun Hu, Bryan Hooi, Bingsheng He, Yinwei Wei

ICML 2025 Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design Zhi Zheng, Zhuoliang Xie, Zhenkun Wang, Bryan Hooi

ICLR 2025 Multi-Label Node Classification with Label Influence Propagation Yifei Sun, Zemin Liu, Bryan Hooi, Yang Yang, Rizal Fathony, Jia Chen, Bingsheng He

AAAI 2025 PhishAgent: A Robust Multimodal Agent for Phishing Webpage Detection Tri Cao, Chengyu Huang, Yuexin Li, Huilin Wang, Amy He, Nay Oo, Bryan Hooi

TMLR 2025 RNA-FrameFlow: Flow Matching for De Novo 3D RNA Backbone Design Rishabh Anand, Chaitanya K. Joshi, Alex Morehead, Arian Rokkum Jamasb, Charles Harris, Simon V Mathis, Kieran Didi, Rex Ying, Bryan Hooi, Pietro Lio

ECML-PKDD 2025 SODA: Out-of-Distribution Detection in Domain-Shifted Point Clouds via Neighborhood Propagation Adam Goodge, Bryan Hooi, Jingyi Liao, Yongyi Su, Wee Siong Ng, Xun Xu, Xulei Yang

TMLR 2025 UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting Juncheng Liu, Chenghao Liu, Gerald Woo, Yiwei Wang, Bryan Hooi, Caiming Xiong, Doyen Sahoo

CVPR 2025 Words or Vision: Do Vision-Language Models Have Blind Faith in Text? Ailin Deng, Tri Cao, Zhirui Chen, Bryan Hooi

ICLRW 2025 Words or Vision: Do Vision-Language Models Have Blind Faith in Text? Ailin Deng, Tri Cao, Zhirui Chen, Bryan Hooi

NeurIPS 2024 $\text{ID}^3$: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition Jianqing Xu, Shen Li, Jiaying Wu, Miao Xiong, Ailin Deng, Jiazhen Ji, Yuge Huang, Guodong Mu, Wenjie Feng, Shouhong Ding, Bryan Hooi

ICMLW 2024 CD-POS: Long Context Generalization in LLMs Through Continuous and Discrete Position Synthesis Zhiyuan Hu, Yuliang Liu, Jinman Zhao, Suyuchen Wang, WangYan, Wei Shen, Chao Yin, Bryan Hooi

ICLR 2024 Can LLMs Express Their Uncertainty? an Empirical Evaluation of Confidence Elicitation in LLMs Miao Xiong, Zhiyuan Hu, Xinyang Lu, Yifei Li, Jie Fu, Junxian He, Bryan Hooi

ICLR 2024 Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision Nan Chen, Zemin Liu, Bryan Hooi, Bingsheng He, Rizal Fathony, Jun Hu, Jia Chen

ICLRW 2024 Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View Jintian Zhang, Xin Xu, Ningyu Zhang, Ruibo Liu, Bryan Hooi, Shumin Deng

NeurIPS 2024 G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V. Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, Bryan Hooi

ICLR 2024 Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning Xiaoxin He, Xavier Bresson, Thomas Laurent, Adam Perold, Yann LeCun, Bryan Hooi

ECCV 2024 Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning Jihai Zhang, Xiang Lan, Xiaoye Qu, Yu Cheng, Mengling Feng, Bryan Hooi

ICLR 2024 Partitioning Message Passing for Graph Fraud Detection Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen

AAAI 2024 PoetryDiffusion: Towards Joint Semantic and Metrical Manipulation in Poetry Generation Zhiyuan Hu, Chumin Liu, Yue Feng, Anh Tuan Luu, Bryan Hooi

ICMLW 2024 RNA-FrameFlow for De Novo 3D RNA Backbone Design Rishabh Anand, Chaitanya K. Joshi, Alex Morehead, Arian Rokkum Jamasb, Charles Harris, Simon V Mathis, Kieran Didi, Bryan Hooi, Pietro Lio

ICMLW 2024 RNA-FrameFlow for De Novo 3D RNA Backbone Design Rishabh Anand, Chaitanya K. Joshi, Alex Morehead, Arian Rokkum Jamasb, Charles Harris, Simon V Mathis, Kieran Didi, Bryan Hooi, Pietro Lio

ECML-PKDD 2024 Reinventing Node-Centric Traffic Forecasting for Improved Accuracy and Efficiency Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann

ICLR 2024 Scalable and Effective Implicit Graph Neural Networks on Large Graphs Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Yiwei Wang, Chaosheng Dong, Xiaokui Xiao

ICLRW 2024 Seeing Is Believing: Mitigating Hallucination in Large Vision-Language Models via CLIP-Guided Decoding Ailin Deng, Zhirui Chen, Bryan Hooi

IJCAI 2024 Truth Table Net: Scalable, Compact & Verifiable Neural Networks with a Dual Convolutional Small Boolean Circuit Networks Form Adrien Benamira, Thomas Peyrin, Trevor Yap, Tristan Guérand, Bryan Hooi

NeurIPS 2024 Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in LLMs Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao, See-Kiong Ng, Anh Tuan Luu, Junxian He, Pang Wei Koh, Bryan Hooi

ICLRW 2024 Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in Large Language Models Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao, See-Kiong Ng, Anh Tuan Luu, Junxian He, Pang Wei Koh, Bryan Hooi

NeurIPSW 2024 UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting Juncheng Liu, Chenghao Liu, Gerald Woo, Yiwei Wang, Bryan Hooi, Caiming Xiong, Doyen Sahoo

ICML 2023 A Generalization of ViT/MLP-Mixer to Graphs Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann Lecun, Xavier Bresson

NeurIPS 2023 Expanding Small-Scale Datasets with Guided Imagination Yifan Zhang, Daquan Zhou, Bryan Hooi, Kai Wang, Jiashi Feng

ICML 2023 GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks Yuwen Li, Miao Xiong, Bryan Hooi

ICML 2023 Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement Ailin Deng, Miao Xiong, Bryan Hooi

NeurIPS 2023 LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann

NeurIPSW 2023 Multimodal Graph Learning for Generative Tasks Minji Yoon, Jing Yu Koh, Bryan Hooi, Russ Salakhutdinov

CVPR 2023 Probabilistic Knowledge Distillation of Face Ensembles Jianqing Xu, Shen Li, Ailin Deng, Miao Xiong, Jiaying Wu, Jiaxiang Wu, Shouhong Ding, Bryan Hooi

NeurIPS 2023 Proximity-Informed Calibration for Deep Neural Networks Miao Xiong, Ailin Deng, Pang Wei W Koh, Jiaying Wu, Shen Li, Jianqing Xu, Bryan Hooi

ICML 2023 Reachability-Aware Laplacian Representation in Reinforcement Learning Kaixin Wang, Kuangqi Zhou, Jiashi Feng, Bryan Hooi, Xinchao Wang

ICML 2023 Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi

ECML-PKDD 2022 ARES: Locally Adaptive Reconstruction-Based Anomaly Scoring Adam Goodge, Bryan Hooi, See-Kiong Ng, Wee Siong Ng

TMLR 2022 Birds of a Feather Trust Together: Knowing When to Trust a Classifier via Adaptive Neighborhood Aggregation Miao Xiong, Shen Li, Wenjie Feng, Ailin Deng, Jihai Zhang, Bryan Hooi

IJCAI 2022 CADET: Calibrated Anomaly Detection for Mitigating Hardness Bias Ailin Deng, Adam Goodge, Lang Yi Ang, Bryan Hooi

LoG 2022 Flashlight: Scalable Link Prediction with Effective Decoders Yiwei Wang, Bryan Hooi, Yozen Liu, Tong Zhao, Zhichun Guo, Neil Shah

LoG 2022 Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction Kuangqi Zhou, Kaixin Wang, Jian Tang, Jiashi Feng, Bryan Hooi, Peilin Zhao, Tingyang Xu, Xinchao Wang

ECML-PKDD 2022 LSCALE: Latent Space Clustering-Based Active Learning for Node Classification Juncheng Liu, Yiwei Wang, Bryan Hooi, Renchi Yang, Xiaokui Xiao

AAAI 2022 LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks Adam Goodge, Bryan Hooi, See-Kiong Ng, Wee Siong Ng

NeurIPS 2022 MGNNI: Multiscale Graph Neural Networks with Implicit Layers Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao

IJCAI 2022 Neural PCA for Flow-Based Representation Learning Shen Li, Bryan Hooi

ECML-PKDD 2022 Probing Spurious Correlations in Popular Event-Based Rumor Detection Benchmarks Jiaying Wu, Bryan Hooi

NeurIPS 2022 Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition Yifan Zhang, Bryan Hooi, Lanqing Hong, Jiashi Feng

ICML 2022 The Geometry of Robust Value Functions Kaixin Wang, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng, Shie Mannor

ECCV 2022 Trust, but Verify: Using Self-Supervised Probing to Improve Trustworthiness Ailin Deng, Shen Li, Miao Xiong, Zhirui Chen, Bryan Hooi

NeurIPS 2021 Adaptive Data Augmentation on Temporal Graphs Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Siddharth Bhatia, Bryan Hooi

NeurIPS 2021 EIGNN: Efficient Infinite-Depth Graph Neural Networks Juncheng Liu, Kenji Kawaguchi, Bryan Hooi, Yiwei Wang, Xiaokui Xiao

AAAI 2021 ExGAN: Adversarial Generation of Extreme Samples Siddharth Bhatia, Arjit Jain, Bryan Hooi

AAAI 2021 Graph Neural Network-Based Anomaly Detection in Multivariate Time Series Ailin Deng, Bryan Hooi

ECML-PKDD 2021 GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs Siddharth Bhatia, Yiwei Wang, Bryan Hooi, Tanmoy Chakraborty

NeurIPS 2021 SSMF: Shifting Seasonal Matrix Factorization Koki Kawabata, Siddharth Bhatia, Rui Liu, Mohit Wadhwa, Bryan Hooi

CVPR 2021 Spherical Confidence Learning for Face Recognition Shen Li, Jianqing Xu, Xiaqing Xu, Pengcheng Shen, Shaoxin Li, Bryan Hooi

ICML 2021 Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing Kaixin Wang, Kuangqi Zhou, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng

NeurIPS 2021 Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning Yifan Zhang, Bryan Hooi, Dapeng Hu, Jian Liang, Jiashi Feng

AAAI 2020 FlowScope: Spotting Money Laundering Based on Graphs Xiangfeng Li, Shenghua Liu, Zifeng Li, Xiaotian Han, Chuan Shi, Bryan Hooi, He Huang, Xueqi Cheng

ICLR 2020 Identifying Through Flows for Recovering Latent Representations Shen Li, Bryan Hooi, Gim Hee Lee

AAAI 2020 Midas: Microcluster-Based Detector of Anomalies in Edge Streams Siddharth Bhatia, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos

ECML-PKDD 2020 Progressive Supervision for Node Classification Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi

IJCAI 2020 Robustness of Autoencoders for Anomaly Detection Under Adversarial Impact Adam Goodge, Bryan Hooi, See-Kiong Ng, Wee Siong Ng

AAAI 2020 TellTail: Fast Scoring and Detection of Dense Subgraphs Bryan Hooi, Kijung Shin, Hemank Lamba, Christos Faloutsos

IJCAI 2019 BeatGAN: Anomalous Rhythm Detection Using Adversarially Generated Time Series Bin Zhou, Shenghua Liu, Bryan Hooi, Xueqi Cheng, Jing Ye

ECML-PKDD 2018 GridWatch: Sensor Placement and Anomaly Detection in the Electrical Grid Bryan Hooi, Dhivya Eswaran, Hyun Ah Song, Amritanshu Pandey, Marko Jereminov, Larry T. Pileggi, Christos Faloutsos

IJCAI 2018 NeuCast: Seasonal Neural Forecast of Power Grid Time Series Pudi Chen, Shenghua Liu, Chuan Shi, Bryan Hooi, Bai Wang, Xueqi Cheng

ECML-PKDD 2018 ONE-M: Modeling the Co-Evolution of Opinions and Network Connections Aastha Nigam, Kijung Shin, Ashwin Bahulkar, Bryan Hooi, David Hachen, Boleslaw K. Szymanski, Christos Faloutsos, Nitesh V. Chawla

ECML-PKDD 2018 Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions Kijung Shin, Jisu Kim, Bryan Hooi, Christos Faloutsos

ECML-PKDD 2017 BeatLex: Summarizing and Forecasting Time Series with Patterns Bryan Hooi, Shenghua Liu, Asim Smailagic, Christos Faloutsos

ECML-PKDD 2017 PowerCast: Mining and Forecasting Power Grid Sequences Hyun Ah Song, Bryan Hooi, Marko Jereminov, Amritanshu Pandey, Larry T. Pileggi, Christos Faloutsos

ECML-PKDD 2017 zooRank: Ranking Suspicious Entities in Time-Evolving Tensors Hemank Lamba, Bryan Hooi, Kijung Shin, Christos Faloutsos, Jürgen Pfeffer

ECML-PKDD 2016 M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees Kijung Shin, Bryan Hooi, Christos Faloutsos