Zhaoxuan Wu

30 papers A* 10A 2Journal 15Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
MineDraft: A Framework for Batch Parallel Speculative Decoding.
CoRR
Zhenwei Tang, Arun Verma, Zijian Zhou, Zhaoxuan Wu, Alok Prakash, Daniela Rus, Bryan Kian Hsiang Low
2025 A* conf
Group-robust Sample Reweighting for Subpopulation Shifts via Influence Functions.
ICLR
Rui Qiao, Zhaoxuan Wu, Jingtan Wang, Pang Wei Koh, Bryan Kian Hsiang Low
2025 J jnl
Group-robust Sample Reweighting for Subpopulation Shifts via Influence Functions.
CoRR
Rui Qiao, Zhaoxuan Wu, Jingtan Wang, Pang Wei Koh, Bryan Kian Hsiang Low
2025 J jnl
Incentivizing Time-Aware Fairness in Data Sharing.
CoRR
Jiangwei Chen, Kieu Thao Nguyen Pham, Rachael Hwee Ling Sim, Arun Verma, Zhaoxuan Wu, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2025 J jnl
MEM1: Learning to Synergize Memory and Reasoning for Efficient Long-Horizon Agents.
CoRR
Zijian Zhou, Ao Qu, Zhaoxuan Wu, Sunghwan Kim, Alok Prakash, Daniela Rus, Jinhua Zhao, Bryan Kian Hsiang Low, Paul Pu Liang
2025 J jnl
NodeChain: Cheap Data Integrity Without Consensus.
IACR Cryptol. ePrint Arch.
Orfeas Stefanos Thyfronitis Litos, Zhaoxuan Wu, Alfredo Musumeci, Songyun Hu, James Helsby, Michael Breza, William Knottenbelt
2025 A* conf
Paid with Models: Optimal Contract Design for Collaborative Machine Learning.
AAAI
Bingchen Wang, Zhaoxuan Wu, Fusheng Liu, Bryan Kian Hsiang Low
2025 — conf
TETRIS: Optimal Draft Token Selection for Batch Speculative Decoding.
ACL (1)
Zhaoxuan Wu, Zijian Zhou, Arun Verma, Alok Prakash, Daniela Rus, Bryan Kian Hsiang Low
2025 J jnl
TETRIS: Optimal Draft Token Selection for Batch Speculative Decoding.
CoRR
Zhaoxuan Wu, Zijian Zhou, Arun Verma, Alok Prakash, Daniela Rus, Bryan Kian Hsiang Low
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 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 J jnl
Dynamic differential privacy-based dataset condensation.
Neurocomputing
Zhaoxuan Wu, Xiaojing Gao, Yongfeng Qian, Yixue Hao, Min Chen
2024 A* conf
Incentive-Aware Federated Learning with Training-Time Model Rewards.
ICLR
Zhaoxuan Wu, Mohammad Mohammadi Amiri, Ramesh Raskar, 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
Localized Zeroth-Order Prompt Optimization.
CoRR
Wenyang Hu, Yao Shu, Zongmin Yu, Zhaoxuan Wu, Xiangqiang Lin, Zhongxiang Dai, See-Kiong Ng, Bryan Kian Hsiang Low
2024 J jnl
Paid with Models: Optimal Contract Design for Collaborative Machine Learning.
CoRR
Bingchen Wang, Zhaoxuan Wu, Fusheng Liu, 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 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: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery.
AISTATS
Xinyi Xu, Zhaoxuan Wu, Arun Verma, Chuan Sheng Foo, 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
2022 A* conf
DAVINZ: Data Valuation using Deep Neural Networks at Initialization.
ICML
Zhaoxuan Wu, Yao Shu, Bryan Kian Hsiang Low
2022 A* conf
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search.
NeurIPS
Yao Shu, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low
2022 J jnl
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search.
CoRR
Yao Shu, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low
2021 J jnl
Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization.
CoRR
Quoc Phong Nguyen, Zhaoxuan Wu, Bryan Kian Hsiang Low, Patrick Jaillet
2021 A conf
Trusted-maximizers entropy search for efficient Bayesian optimization.
UAI
Quoc Phong Nguyen, Zhaoxuan Wu, Bryan Kian Hsiang Low, Patrick Jaillet
2021 A* conf
Validation Free and Replication Robust Volume-based Data Valuation.
NeurIPS
Xinyi Xu, Zhaoxuan Wu, Chuan Sheng Foo, Bryan Kian Hsiang Low