Foo, Chuan Sheng

54 publications

ICLRW 2025 Broaden Your SCOPE! Efficient Conversation Planning for LLMs Using Semantic Space Zhiliang Chen, Xinyuan Niu, Chuan-Sheng Foo, Bryan Kian Hsiang Low

ICLR 2025 Broaden Your SCOPE! Efficient Multi-Turn Conversation Planning for LLMs with Semantic Space Zhiliang Chen, Xinyuan Niu, Chuan-Sheng Foo, Bryan Kian Hsiang Low

CVPR 2025 CADCrafter: Generating Computer-Aided Design Models from Unconstrained Images Cheng Chen, Jiacheng Wei, Tianrun Chen, Chi Zhang, Xiaofeng Yang, Shangzhan Zhang, Bingchen Yang, Chuan-Sheng Foo, Guosheng Lin, Qixing Huang, Fayao Liu

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

ICLRW 2025 DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks Zhiliang Chen, Gregory Kang Ruey Lau, Chuan-Sheng Foo, Bryan Kian Hsiang Low

ICLR 2025 Evidential Learning-Based Certainty Estimation for Robust Dense Feature Matching Lile Cai, Chuan-Sheng Foo, Xun Xu, Zaiwang Gu, Jun Cheng, Xulei Yang

ICCV 2025 FIND: Few-Shot Anomaly Inspection with Normal-Only Multi-Modal Data Yiting Li, Fayao Liu, Jingyi Liao, Sichao Tian, Chuan-Sheng Foo, Xulei Yang

NeurIPS 2025 Incentivizing Time-Aware Fairness in Data Sharing Jiangwei Chen, Kieu Thao Nguyen Pham, Rachael Hwee Ling Sim, Arun Verma, Zhaoxuan Wu, Chuan-Sheng Foo, Bryan Kian Hsiang Low

ICML 2025 NICE Data Selection for Instruction Tuning in LLMs with Non-Differentiable Evaluation Metric Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Pang Wei Koh, Chuan-Sheng Foo, Bryan Kian Hsiang Low

ICLRW 2025 NICE: Non-Differentiable Evaluation Metric-Based Data Selection for Instruction Tuning Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Pang Wei Koh, Chuan-Sheng Foo, Bryan Kian Hsiang Low

ICLR 2025 On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning Yongyi Su, Yushu Li, Nanqing Liu, Kui Jia, Xulei Yang, Chuan-Sheng Foo, Xun Xu

ICLR 2025 Robust-PIFu: Robust Pixel-Aligned Implicit Function for 3D Human Digitalization from a Single Image Kennard Chan, Fayao Liu, Guosheng Lin, Chuan-Sheng Foo, Weisi Lin

ICLRW 2025 SCOPE: Improving LLM Conversations with Efficient Semantic Space Planning Zhiliang Chen, Xinyuan Niu, Chuan-Sheng Foo, Bryan Kian Hsiang Low

ECCV 2024 3DFG-PIFu: 3D Feature Grids for Human Digitization from Sparse Views Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin

ICLR 2024 A Unified Framework for Bayesian Optimization Under Contextual Uncertainty Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low

NeurIPS 2024 Data Distribution Valuation Xinyi Xu, Shuaiqi Wang, Chuan-Sheng Foo, Bryan Kian Hsiang Low, Giulia Fanti

AAAI 2024 Fine Structure-Aware Sampling: A New Sampling Training Scheme for Pixel-Aligned Implicit Models in Single-View Human Reconstruction Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin

ICML 2024 Helpful or Harmful Data? Fine-Tuning-Free Shapley Attribution for Explaining Language Model Predictions Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Chuan-Sheng Foo, Bryan Kian Hsiang Low

TMLR 2024 Hybrid Active Learning with Uncertainty-Weighted Embeddings Yinan He, Lile Cai, Jingyi Liao, Chuan-Sheng Foo

WACV 2024 PromptAD: Zero-Shot Anomaly Detection Using Text Prompts Yiting Li, Adam Goodge, Fayao Liu, Chuan-Sheng Foo

ICML 2024 Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Unsupervised Domain Adaptation Dapeng Hu, Jian Liang, Xinchao Wang, Chuan-Sheng Foo

CVPR 2024 R-Cyclic Diffuser: Reductive and Cyclic Latent Diffusion for 3D Clothed Human Digitalization Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin

CVPR 2024 REACTO: Reconstructing Articulated Objects from a Single Video Chaoyue Song, Jiacheng Wei, Chuan Sheng Foo, Guosheng Lin, Fayao Liu

CVPR 2024 Sculpt3D: Multi-View Consistent Text-to-3D Generation with Sparse 3D Prior Cheng Chen, Xiaofeng Yang, Fan Yang, Chengzeng Feng, Zhoujie Fu, Chuan-Sheng Foo, Guosheng Lin, Fayao Liu

ICML 2024 Towards AutoAI: Optimizing a Machine Learning System with Black-Box and Differentiable Components Zhiliang Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low

NeurIPS 2024 Towards Reliable Model Selection for Unsupervised Domain Adaptation: An Empirical Study and a Certified Baseline Dapeng Hu, Mi Luo, Jian Liang, Chuan-Sheng Foo

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

CVPR 2024 Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias Wenyu Zhang, Qingmu Liu, Felix Ong Wei Cong, Mohamed Ragab, Chuan-Sheng Foo

ICMLW 2024 Waterfall: Framework for Robust and Scalable Text Watermarking Gregory Kang Ruey Lau, Xinyuan Niu, Hieu Dao, Jiangwei Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low

TMLR 2024 When Low-Vision Task Meets Dense Prediction Tasks with Less Data: An Auxiliary Self-Trained Geometry Regularization Zaiwang Gu, Weide Liu, Xulei Yang, Chuan-Sheng Foo, Jun Cheng

NeurIPS 2023 Bayesian Optimization with Cost-Varying Variable Subsets Sebastian Tay, Chuan Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low

MLJ 2023 Diverse and Consistent Multi-View Networks for Semi-Supervised Regression Cuong Manh Nguyen, Arun Raja, Le Zhang, Xun Xu, Balagopal Unnikrishnan, Mohamed Ragab, Kangkang Lu, Chuan-Sheng Foo

AISTATS 2023 FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery Xinyi Xu, Zhaoxuan Wu, Arun Verma, Chuan Sheng Foo, Bryan Kian Hsiang Low

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

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

NeurIPS 2023 Model Shapley: Equitable Model Valuation with Black-Box Access Xinyi Xu, Thanh Lam, Chuan Sheng Foo, Bryan Kian Hsiang Low

AISTATS 2023 No-Regret Sample-Efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities Sebastian Shenghong Tay, Quoc Phong Nguyen, Chuan Sheng Foo, Bryan Kian Hsiang Low

AAAI 2023 Probably Approximate Shapley Fairness with Applications in Machine Learning Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Bryan Kian Hsiang Low

NeurIPSW 2023 Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Domain Adaptation Dapeng Hu, Jian Liang, Xinchao Wang, Chuan-Sheng Foo

ICCV 2023 Rethinking the Role of Pre-Trained Networks in Source-Free Domain Adaptation Wenyu Zhang, Li Shen, Chuan-Sheng Foo

NeurIPSW 2023 Simplifying and Stabilizing Model Selection in Unsupervised Domain Adaptation Dapeng Hu, Mi Luo, Jian Liang, Chuan-Sheng Foo

ICML 2022 Efficient Distributionally Robust Bayesian Optimization with Worst-Case Sensitivity Sebastian Shenghong Tay, Chuan Sheng Foo, Urano Daisuke, Richalynn Leong, Bryan Kian Hsiang Low

IJCAI 2022 Few-Shot Adaptation of Pre-Trained Networks for Domain Shift Wenyu Zhang, Li Shen, Wanyue Zhang, Chuan-Sheng Foo

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

AAAI 2022 Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards Sebastian Shenghong Tay, Xinyi Xu, Chuan Sheng Foo, Bryan Kian Hsiang Low

ICLR 2021 ARMOURED: Adversarially Robust MOdels Using Unlabeled Data by REgularizing Diversity Kangkang Lu, Cuong Manh Nguyen, Xun Xu, Kiran Krishnamachari, Yu Jing Goh, Chuan-Sheng Foo

NeurIPS 2021 Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo, Bryan Kian Hsiang Low

CVPR 2021 Revisiting Superpixels for Active Learning in Semantic Segmentation with Realistic Annotation Costs Lile Cai, Xun Xu, Jun Hao Liew, Chuan Sheng Foo

NeurIPS 2021 Validation Free and Replication Robust Volume-Based Data Valuation Xinyi Xu, Zhaoxuan Wu, Chuan Sheng Foo, Bryan Kian Hsiang Low

ICLR 2019 Optimistic Mirror Descent in Saddle-Point Problems: Going the Extra (gradient) Mile Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras

ICLR 2019 The Unusual Effectiveness of Averaging in GAN Training Yasin, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar

ICML 2009 A Majorization-Minimization Algorithm for (multiple) Hyperparameter Learning Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng

ICML 2009 Proximal Regularization for Online and Batch Learning Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo

NeurIPS 2007 Efficient Multiple Hyperparameter Learning for Log-Linear Models Chuan-sheng Foo, Chuong B. Do, Andrew Y. Ng