Xiaoqiang Lin - RankMe

27 papers A* 11Journal 14Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	W&D:Scaling Parallel Tool Calling for Efficient Deep Research Agents. CoRR Xiaoqiang Lin, Jun Hao Liew, Silvio Savarese, Junnan Li
2025	J	`jnl`	Active Human Feedback Collection via Neural Contextual Dueling Bandits. CoRR Arun Verma, Xiaoqiang Lin, Zhongxiang Dai, Daniela Rus, Bryan Kian Hsiang Low
2025	J	`jnl`	ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment. CoRR Xiaoqiang Lin, Arun Verma, Zhongxiang Dai, Daniela Rus, See-Kiong Ng, Bryan Kian Hsiang Low
2025	A*	`conf`	Efficient Top-m Data Values Identification for Data Selection. ICLR Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Bryan Kian Hsiang Low
2025	A*	`conf`	NICE Data Selection for Instruction Tuning in LLMs with Non-differentiable Evaluation Metric. ICML Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Pang Wei Koh, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2025	A*	`conf`	Neural Dueling Bandits: Preference-Based Optimization with Human Feedback. ICLR Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low
2025	J	`jnl`	REFRAG: Rethinking RAG based Decoding. CoRR Xiaoqiang Lin, Aritra Ghosh, Bryan Kian Hsiang Low, Anshumali Shrivastava, Vijai Mohan
2025	—	`conf`	Uncovering Scaling Laws for Large Language Models via Inverse Problems. EMNLP (Findings) Arun Verma, Zhaoxuan Wu, Zijian Zhou, Xiaoqiang Lin, Zhiliang Chen, Rachael Hwee Ling Sim, Rui Qiao, Jingtan Wang, Nhung Bui, Xinyuan Niu, Wenyang Hu, Gregory Kang Ruey Lau, Zi-Yu Khoo, Zitong Zhao, Xinyi Xu, Apivich Hemachandra, See-Kiong Ng, Bryan Kian Hsiang Low
2025	J	`jnl`	Uncovering Scaling Laws for Large Language Models via Inverse Problems. CoRR Arun Verma, Zhaoxuan Wu, Zijian Zhou, Xiaoqiang Lin, Zhiliang Chen, Rachael Hwee Ling Sim, Rui Qiao, Jingtan Wang, Nhung Bui, Xinyuan Niu, Wenyang Hu, Gregory Kang Ruey Lau, Zi-Yu Khoo, Zitong Zhao, Xinyi Xu, Apivich Hemachandra, See-Kiong Ng, Bryan Kian Hsiang Low
2024	A*	`conf`	DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning. NeurIPS Zijian Zhou, Xiaoqiang Lin, Xinyi Xu, Alok Prakash, Daniela Rus, Bryan Kian Hsiang Low
2024	J	`jnl`	DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning. CoRR Zijian Zhou, Xiaoqiang Lin, Xinyi Xu, Alok Prakash, Daniela Rus, Bryan Kian Hsiang Low
2024	J	`jnl`	Data-Centric AI in the Age of Large Language Models. CoRR Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low
2024	A*	`conf`	Distributionally Robust Data Valuation. ICML Xiaoqiang Lin, Xinyi Xu, Zhaoxuan Wu, See-Kiong Ng, Bryan Kian Hsiang Low
2024	A*	`conf`	Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions. ICML Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2024	J	`jnl`	Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions. CoRR Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2024	A*	`conf`	Localized Zeroth-Order Prompt Optimization. NeurIPS Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low
2024	J	`jnl`	Neural Dueling Bandits. CoRR Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low
2024	—	`conf`	Position Paper: Data-Centric AI in the Age of Large Language Models. EMNLP (Findings) Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low
2024	A*	`conf`	Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars. NeurIPS Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low
2024	J	`jnl`	Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars. CoRR Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low
2024	J	`jnl`	Prompt Optimization with Human Feedback. CoRR Xiaoqiang Lin, Zhongxiang Dai, Arun Verma, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low
2024	A*	`conf`	Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers. ICML Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low
2023	A*	`conf`	Fair yet Asymptotically Equal Collaborative Learning. ICML Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2023	J	`jnl`	Fair yet Asymptotically Equal Collaborative Learning. CoRR Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2023	J	`jnl`	Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients. CoRR Yao Shu, Xiaoqiang Lin, Zhongxiang Dai, Bryan Kian Hsiang Low
2023	J	`jnl`	Use Your INSTINCT: INSTruction optimization usIng Neural bandits Coupled with Transformers. CoRR Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai, Wenyang Hu, Yao Shu, See-Kiong Ng, Patrick Jaillet, Bryan Kian Hsiang Low
2020	A*	`conf`	Joint Representation Learning of Legislator and Legislation for Roll Call Prediction. IJCAI Yuqiao Yang, Xiaoqiang Lin, Geng Lin, Zengfeng Huang, Changjian Jiang, Zhongyu Wei