Rachael Hwee Ling Sim

19 papers A* 7A 1Journal 9Unranked 2
YearRankTypeTitle / Venue / Authors
2025 A conf
DUPRE: Data Utility Prediction for Efficient Data Valuation.
AAMAS
Kieu Thao Nguyen Pham, Rachael Hwee Ling Sim, Quoc Phong Nguyen, See-Kiong Ng, Bryan Kian Hsiang Low
2025 J jnl
DUPRE: Data Utility Prediction for Efficient Data Valuation.
CoRR
Kieu Thao Nguyen Pham, Rachael Hwee Ling Sim, Quoc Phong Nguyen, See-Kiong Ng, 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 — 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
2025 J jnl
WaterDrum: Watermarking for Data-centric Unlearning Metric.
CoRR
Xinyang Lu, Xinyuan Niu, Gregory Kang Ruey Lau, Bui Thi Cam Nhung, Rachael Hwee Ling Sim, Fanyu Wen, Chuan-Sheng Foo, 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
DeRDaVa: Deletion-Robust Data Valuation for Machine Learning.
AAAI
Xiao Tian, Rachael Hwee Ling Sim, Jue Fan, Bryan Kian Hsiang Low
2024 A* conf
Deletion-Anticipative Data Selection with a Limited Budget.
ICML
Rachael Hwee Ling Sim, Jue Fan, Xiao Tian, Patrick Jaillet, Bryan Kian Hsiang Low
2024 J jnl
Incentives in Private Collaborative Machine Learning.
CoRR
Rachael Hwee Ling Sim, Yehong Zhang, Trong Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet
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
2023 J jnl
DeRDaVa: Deletion-Robust Data Valuation for Machine Learning.
CoRR
Xiao Tian, Rachael Hwee Ling Sim, Jue Fan, Bryan Kian Hsiang Low
2023 A* conf
Incentives in Private Collaborative Machine Learning.
NeurIPS
Rachael Hwee Ling Sim, Yehong Zhang, Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet
2023 A* conf
Probably Approximate Shapley Fairness with Applications in Machine Learning.
AAAI
Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Bryan Kian Hsiang Low
2022 A* conf
Data Valuation in Machine Learning: "Ingredients", Strategies, and Open Challenges.
IJCAI
Rachael Hwee Ling Sim, Xinyi Xu, Bryan Kian Hsiang Low
2022 J jnl
Probably Approximate Shapley Fairness with Applications in Machine Learning.
CoRR
Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Kian Hsiang Low
2021 A* conf
Collaborative Bayesian Optimization with Fair Regret.
ICML
Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet
2020 A* conf
Collaborative Machine Learning with Incentive-Aware Model Rewards.
ICML
Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, Bryan Kian Hsiang Low
2020 J jnl
Collaborative Machine Learning with Incentive-Aware Model Rewards.
CoRR
Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, Bryan Kian Hsiang Low