Joint Representation Learning of Legislator and Legislation for Roll Call Prediction. - Yuqiao Yang; Xiaoqiang Lin; Geng Lin; Zengfeng Huang; Changjian Jiang; Zhongyu Wei (IJCAI, 2020)

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

Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients. - Yao Shu; Xiaoqiang Lin; Zhongxiang Dai; Bryan Kian Hsiang Low (CoRR, 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 (CoRR, 2023)

Position Paper: Data-Centric AI in the Age of Large Language Models. - Xinyi Xu; Zhaoxuan Wu; Rui Qiao 006; Arun Verma; Yao Shu; Jingtan Wang 001; Xinyuan Niu 001; Zhenfeng He; Jiangwei Chen 001; Zijian Zhou; Gregory Kang Ruey Lau; Hieu Dao; et al. (EMNLP (Findings), 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 (ICML, 2024)

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

Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions. - Jingtan Wang 001; Xiaoqiang Lin; Rui Qiao 006; Chuan-Sheng Foo; Bryan Kian Hsiang Low (ICML, 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 (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 (NeurIPS, 2024)

DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning. - Zijian Zhou; Xiaoqiang Lin; Xinyi Xu; Alok Prakash; Daniela Rus; Bryan Kian Hsiang Low (NeurIPS, 2024)

Prompt Optimization with Human Feedback. - Xiaoqiang Lin; Zhongxiang Dai; Arun Verma; See-Kiong Ng; Patrick Jaillet; Bryan Kian Hsiang Low (CoRR, 2024)

Data-Centric AI in the Age of Large Language Models. - Xinyi Xu; Zhaoxuan Wu; Rui Qiao 006; Arun Verma; Yao Shu; Jingtan Wang 001; Xinyuan Niu 001; Zhenfeng He; Jiangwei Chen 001; Zijian Zhou; Gregory Kang Ruey Lau; Hieu Dao; et al. (CoRR, 2024)

Neural Dueling Bandits. - Arun Verma; Zhongxiang Dai; Xiaoqiang Lin; Patrick Jaillet; Bryan Kian Hsiang Low (CoRR, 2024)

Efficient Top-m Data Values Identification for Data Selection. - Xiaoqiang Lin; Xinyi Xu; See-Kiong Ng; Bryan Kian Hsiang Low (ICLR, 2025)

Neural Dueling Bandits: Preference-Based Optimization with Human Feedback. - Arun Verma; Zhongxiang Dai; Xiaoqiang Lin; Patrick Jaillet; Bryan Kian Hsiang Low (ICLR, 2025)

Active Human Feedback Collection via Neural Contextual Dueling Bandits. - Arun Verma; Xiaoqiang Lin; Zhongxiang Dai; Daniela Rus; Bryan Kian Hsiang Low (CoRR, 2025)

ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment. - Xiaoqiang Lin; Arun Verma; Zhongxiang Dai; Daniela Rus; See-Kiong Ng; Bryan Kian Hsiang Low (CoRR, 2025)