Rachael Hwee Ling Sim

According to our database, Rachael Hwee Ling Sim authored at least 18 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

De-attribute to Forget for LLM Unlearning.

Xinyang Lu, Jiabao Pan, Rachael Hwee Ling Sim, See-Kiong Ng, Anthony Kum Hoe Tung, Bryan Kian Hsiang Low

CoRR, May, 2026

Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning.

Rachael Hwee Ling Sim, Jue Fan, Xiao Tian, Xinyi Xu, Patrick Jaillet, Bryan Kian Hsiang Low

CoRR, May, 2026

Is Data Shapley Not Better than Random in Data Selection? Ask NASH.

Xiao Tian, Jue Fan, Rachael Hwee Ling Sim, Zixuan Wang, Nancy F. Chen, Bryan Kian Hsiang Low

CoRR, May, 2026

INO-SGD: Addressing Utility Imbalance under Individualized Differential Privacy.

Xiao Tian, Jue Fan, Rachael Hwee Ling Sim, Bryan Kian Hsiang Low

CoRR, May, 2026

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

CoRR, October, 2025

WaterDrum: Watermarking for Data-centric Unlearning Metric.

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

CoRR, May, 2025

DUPRE: Data Utility Prediction for Efficient Data Valuation.

Kieu Thao Nguyen Pham, Rachael Hwee Ling Sim, Quoc Phong Nguyen, See-Kiong Ng, Bryan Kian Hsiang Low

Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, 2025

Uncovering Scaling Laws for Large Language Models via Inverse Problems.

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

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

2024

Data-Centric AI in the Age of Large Language Models.

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

CoRR, 2024

Incentives in Private Collaborative Machine Learning.

Rachael Hwee Ling Sim, Yehong Zhang, Trong Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet

CoRR, 2024

Deletion-Anticipative Data Selection with a Limited Budget.

Rachael Hwee Ling Sim, Jue Fan, Xiao Tian, Patrick Jaillet, Bryan Kian Hsiang Low

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Position Paper: Data-Centric AI in the Age of Large Language Models.

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

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

DeRDaVa: Deletion-Robust Data Valuation for Machine Learning.

Xiao Tian, Rachael Hwee Ling Sim, Jue Fan, Bryan Kian Hsiang Low

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Incentives in Private Collaborative Machine Learning.

Rachael Hwee Ling Sim, Yehong Zhang, Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Data Valuation in Machine Learning: "Ingredients", Strategies, and Open Challenges.

Rachael Hwee Ling Sim, Xinyi Xu, Bryan Kian Hsiang Low

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Collaborative Bayesian Optimization with Fair Regret.

Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Collaborative Machine Learning with Incentive-Aware Model Rewards.

Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, Bryan Kian Hsiang Low

Proceedings of the 37th International Conference on Machine Learning, 2020