Ng, See Kiong

65 publications

NeurIPS 2025 Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Mingzhe Du, Anh Tuan Luu, Yue Liu, Yuhao Qing, Dong Huang, Xinyi He, Qian Liu, Zejun Ma, See-Kiong Ng

AAAI 2025 Aligning Large Language Models for Faithful Integrity Against Opposing Argument Yong Zhao, Yang Deng, See-Kiong Ng, Tat-Seng Chua

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

ICLR 2025 Confidence Elicitation: A New Attack Vector for Large Language Models Brian Formento, Chuan-Sheng Foo, See-Kiong Ng

NeurIPS 2025 Continual Multimodal Contrastive Learning Xiaohao Liu, Xiaobo Xia, See-Kiong Ng, Tat-Seng Chua

ICLRW 2025 DDPS: Discrete Diffusion Posterior Sampling for Paths in Layered Graphs Hao Luan, See-Kiong Ng, Chun Kai Ling

NeurIPS 2025 EffiBench-X: A Multi-Language Benchmark for Measuring Efficiency of LLM-Generated Code Yuhao Qing, Boyu Zhu, Mingzhe Du, Zhijiang Guo, Terry Yue Zhuo, Qianru Zhang, Jie M. Zhang, Heming Cui, Siu Ming Yiu, Dong Huang, See-Kiong Ng, Anh Tuan Luu

ICLR 2025 Efficient Inference for Large Language Model-Based Generative Recommendation Xinyu Lin, Chaoqun Yang, Wenjie Wang, Yongqi Li, Cunxiao Du, Fuli Feng, See-Kiong Ng, Tat-Seng Chua

ICLR 2025 Efficient Top-M Data Values Identification for Data Selection Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Bryan Kian Hsiang Low

ICML 2025 Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models Yao Shu, Wenyang Hu, See-Kiong Ng, Bryan Kian Hsiang Low, Fei 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 L-MTP: Leap Multi-Token Prediction Beyond Adjacent Context for Large Language Models Xiaohao Liu, Xiaobo Xia, Weixiang Zhao, Manyi Zhang, Xianzhi Yu, Xiu Su, Shuo Yang, See-Kiong Ng, Tat-Seng Chua

ICML 2025 Leveraging Diffusion Model as Pseudo-Anomalous Graph Generator for Graph-Level Anomaly Detection Jinyu Cai, Yunhe Zhang, Fusheng Liu, See-Kiong Ng

AAAI 2025 Mixture of Experts as Representation Learner for Deep Multi-View Clustering Yunhe Zhang, Jinyu Cai, Zhihao Wu, Pengyang Wang, See-Kiong Ng

AAAI 2025 Motion-Aware Contrastive Learning for Temporal Panoptic Scene Graph Generation Thong Thanh Nguyen, Xiaobao Wu, Yi Bin, Cong-Duy T. Nguyen, See-Kiong Ng, Anh Tuan Luu

AAAI 2025 Multi-Scale Contrastive Learning for Video Temporal Grounding Thong Thanh Nguyen, Yi Bin, Xiaobao Wu, Zhiyuan Hu, Cong-Duy T. Nguyen, See-Kiong Ng, Anh Tuan Luu

ICLRW 2025 OPPA: OPtimizing PArallelism for Language Model Training Apivich Hemachandra, Yizhan Han, See-Kiong Ng, Bryan Kian Hsiang Low

ICLR 2025 PIED: Physics-Informed Experimental Design for Inverse Problems Apivich Hemachandra, Gregory Kang Ruey Lau, See-Kiong Ng, Bryan Kian Hsiang Low

NeurIPS 2025 Self-Perturbed Anomaly-Aware Graph Dynamics for Multivariate Time-Series Anomaly Detection Jinyu Cai, Yuan Xie, Glynnis Lim, Yifang Yin, Roger Zimmermann, See-Kiong Ng

IJCAI 2025 Taking STEPS Forward: Enhancing Online Peer-Counseling with Schema Therapy via Socratic Questioning Beng Heng Ang, Sujatha Das Gollapalli, See-Kiong Ng

AAAI 2025 Towards Verifiable Text Generation with Generative Agent Bin Ji, Huijun Liu, Mingzhe Du, Shasha Li, Xiaodong Liu, Jun Ma, Jie Yu, See-Kiong Ng

AAAI 2024 Chain-of-Thought Improves Text Generation with Citations in Large Language Models Bin Ji, Huijun Liu, Mingzhe Du, See-Kiong Ng

NeurIPSW 2024 Dipper: Diversity in Prompts for Producing Large Language Model Ensembles in Reasoning Tasks Gregory Kang Ruey Lau, Wenyang Hu, Liu Diwen, Chen Jizhuo, See-Kiong Ng, Bryan Kian Hsiang Low

ICML 2024 Distributionally Robust Data Valuation Xiaoqiang Lin, Xinyi Xu, Zhaoxuan Wu, See-Kiong Ng, Bryan Kian Hsiang Low

NeurIPSW 2024 Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models Yao Shu, Wenyang Hu, See-Kiong Ng, Bryan Kian Hsiang Low, Fei Yu

IJCAI 2024 From 2D to 3D: AISG-SLA Visual Localization Challenge Jialin Gao, Bill Ong, Darld Lwi, Zhen Hao Ng, Xun Wei Yee, Mun-Thye Mak, Wee Siong Ng, See-Kiong Ng, Hui Ying Teo, Victor Khoo, Georg Bökman, Johan Edstedt, Kirill Brodt, Clémentin Boittiaux, Maxime Ferrera, Stepan Konev

AAAI 2024 From Static to Dynamic: Knowledge Metabolism for Large Language Models Mingzhe Du, Anh Tuan Luu, Bin Ji, See-Kiong Ng

IJCAI 2024 LG-FGAD: An Effective Federated Graph Anomaly Detection Framework Jinyu Cai, Yunhe Zhang, Jicong Fan, See-Kiong Ng

NeurIPS 2024 Localized Zeroth-Order Prompt Optimization Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low

ICMLW 2024 Localized Zeroth-Order Prompt Optimization Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low

ICLRW 2024 Magic: Investigation of Large Language Model Powered Multi-Agent in Cognition, Adaptability, Rationality and Collaboration Lin Xu, Zhiyuan Hu, Daquan Zhou, Hongyu Ren, Zhen Dong, Kurt Keutzer, See-Kiong Ng, Jiashi Feng

NeurIPS 2024 Mercury: A Code Efficiency Benchmark for Code Large Language Models Mingzhe Du, Luu Anh Tuan, Bin Ji, Qian Liu, See-Kiong Ng

ECCV 2024 Meta-Optimized Angular Margin Contrastive Framework for Video-Language Representation Learning Thong Thanh Nguyen, Yi Bin, Xiaobao Wu, Xinshuai Dong, Zhiyuan Hu, Khoi M Le, Cong-Duy Nguyen, See Kiong Ng, Anh Tuan Luu

ICMLW 2024 PIED: Physics-Informed Experimental Design for Inverse Problems Apivich Hemachandra, Gregory Kang Ruey Lau, See-Kiong Ng, Bryan Kian Hsiang Low

ICLR 2024 PINNACLE: PINN Adaptive ColLocation and Experimental Points Selection Gregory Kang Ruey Lau, Apivich Hemachandra, See-Kiong Ng, Bryan Kian Hsiang Low

ICMLW 2024 PINNACLE: PINN Adaptive ColLocation and Experimental Points Selection Gregory Kang Ruey Lau, Apivich Hemachandra, See-Kiong Ng, Bryan Kian Hsiang Low

ICLR 2024 Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents Yang Deng, Wenxuan Zhang, Wai Lam, See-Kiong Ng, Tat-Seng Chua

NeurIPS 2024 Prompt Optimization with EASE? Efficient Ordering-Aware Automated Selection of Exemplars Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low

ICMLW 2024 Prompt Optimization with EASE? Efficient Ordering-Aware Automated Selection of Exemplars Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low

ICMLW 2024 Prompt Optimization with Human Feedback Xiaoqiang Lin, Zhongxiang Dai, Arun Verma, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low

AAAI 2024 READ-PVLA: Recurrent Adapter with Partial Video-Language Alignment for Parameter-Efficient Transfer Learning in Low-Resource Video-Language Modeling Thong Nguyen, Xiaobao Wu, Xinshuai Dong, Khoi M. Le, Zhiyuan Hu, Cong-Duy Nguyen, See-Kiong Ng, Anh Tuan Luu

ICLR 2024 Topic Modeling as Multi-Objective Contrastive Optimization Thong Thanh Nguyen, Xiaobao Wu, Xinshuai Dong, Cong-Duy T Nguyen, See-Kiong Ng, Anh Tuan Luu

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

TMLR 2024 Uniformly Distributed Feature Representations for Fair and Robust Learning Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo

ICML 2024 Use Your INSTINCT: INSTruction Optimization for LLMs usIng Neural Bandits Coupled with Transformers Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low

IJCAI 2023 COOL, a Context Outlooker, and Its Application to Question Answering and Other Natural Language Processing Tasks Fangyi Zhu, See-Kiong Ng, Stéphane Bressan

TMLR 2023 Data-Free Diversity-Based Ensemble Selection for One-Shot Federated Learning Naibo Wang, Wenjie Feng, Yuchen Deng, Moming Duan, Fusheng Liu, See-Kiong Ng

ICML 2023 Fair yet Asymptotically Equal Collaborative Learning Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Chuan-Sheng Foo, Bryan Kian Hsiang Low

AAAI 2023 Generating Reflective Questions for Engaging Gallery Visitors in ArtMuse Sujatha Das Gollapalli, Mingzhe Du, See-Kiong Ng

TMLR 2023 Mitigating Real-World Distribution Shifts in the Fourier Domain Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo

NeurIPSW 2023 PINNACLE: PINN Adaptive ColLocation and Experimental Points Selection Gregory Kang Ruey Lau, Apivich Hemachandra, See-Kiong Ng, Bryan Kian Hsiang Low

NeurIPSW 2023 Solving Math Word Problems with Reexamination Yi Bin, Wenhao Shi, Yujuan Ding, Yang Yang, See-Kiong Ng

ICML 2023 Training-Free Neural Active Learning with Initialization-Robustness Guarantees Apivich Hemachandra, Zhongxiang Dai, Jasraj Singh, See-Kiong Ng, Bryan Kian Hsiang Low

NeurIPSW 2023 Use Your INSTINCT: INSTruction Optimization usIng Neural Bandits Coupled with Transformers Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low

WACV 2022 A Context-Enriched Satellite Imagery Dataset and an Approach for Parking Lot Detection Yifang Yin, Wenmiao Hu, An Tran, Hannes Kruppa, Roger Zimmermann, See-Kiong Ng

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

TMLR 2022 Fourier Sensitivity and Regularization of Computer Vision Models Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo

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

AAAI 2022 PaintTeR: Automatic Extraction of Text Spans for Generating Art-Centered Questions Sujatha Das Gollapalli, See-Kiong Ng, Ying Kiat Tham, Shan Shan Chow, Jia Min Wong, Kevin Lim

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

AAAI 2011 Integrating Community Question and Answer Archives Wei Wei, Gao Cong, Xiaoli Li, See-Kiong Ng, Guohui Li

IJCAI 2011 Positive Unlabeled Leaning for Time Series Classification Minh Nhut Nguyen, Xiaoli Li, See-Kiong Ng

ECML-PKDD 2009 MACs: Multi-Attribute Co-Clusters with High Correlation Information Kelvin Sim, Vivekanand Gopalkrishnan, Hon Nian Chua, See-Kiong Ng

IJCAI 2007 Learning to Identify Unexpected Instances in the Test Set Xiaoli Li, Bing Liu, See-Kiong Ng