I am a PhD student at National University of Singapore, advised by Prof. Bryan Low, Dr. Chuan-Sheng Foo, Dr. Nancy Chen, and Dr. Zhengyuan. My research is supported by the A*STAR Computing and Information Science (ACIS) Scholarship. I was fortunate to intern with Apple's Video Engineering team in San Diego, where I worked under Manjot Singh Bilkhu. My research interests lie in data-centric language modeling and agentic post-training.
Publications and preprints
Papers sorted by recency.
Scaling Near-Optimal SFT-RL Annotation Budget Allocation from Small to Large LLMs
Jingtan Wang, Arun Verma, Xiaoqiang Lin, Zhengyuan Liu, Nancy F. Chen, Daniela Rus, Bryan Kian Hsiang Low
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2026
arXiv / bibtex
Jingtan Wang, Arun Verma, Xiaoqiang Lin, Zhengyuan Liu, Nancy F. Chen, Daniela Rus, Bryan Kian Hsiang Low
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2026
arXiv / bibtex
RISED: RubrIcs for agentic multi-environment Selection and sElf-Distillation
Jingtan Wang, Sirajul Salekin, Young mok Jung, Javier Movellan, Bryan Kian Hsiang Low, Manjot Bilkhu
arXiv preprint, 2026
Work done during my internship at Apple Video Engineering.
arXiv / bibtex
Jingtan Wang, Sirajul Salekin, Young mok Jung, Javier Movellan, Bryan Kian Hsiang Low, Manjot Bilkhu
arXiv preprint, 2026
Work done during my internship at Apple Video Engineering.
arXiv / bibtex
EULoInf: Efficient Hessian-Free Entropy Based Uncertainty-Aware Data Influence Approximation
Runxin Cai*, Jingtan Wang*, Bryan Kian Hsiang Low
Findings of the Association for Computational Linguistics: ACL, 2026
paper / bibtex
Runxin Cai*, Jingtan Wang*, Bryan Kian Hsiang Low
Findings of the Association for Computational Linguistics: ACL, 2026
paper / bibtex
NICE Data Selection for Instruction Tuning in LLMs with Non-differentiable Evaluation Metric
Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Pang Wei Koh, Chuan-sheng Foo, Bryan Kian Hsiang Low
International Conference on Machine Learning (ICML), 2025
code / bibtex
Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Pang Wei Koh, Chuan-sheng Foo, Bryan Kian Hsiang Low
International Conference on Machine Learning (ICML), 2025
code / bibtex
Source Attribution for Large Language Model-Generated Data
Xinyang Lu*, Jingtan Wang*, Zitong Zhao*, Zhongxiang Dai, Chuan-Sheng Foo, See-Kiong Ng, Bryan Kian Hsiang Low
Annual Meeting of the Association for Computational Linguistics (ACL), Findings, 2025
arXiv / code / bibtex
Xinyang Lu*, Jingtan Wang*, Zitong Zhao*, Zhongxiang Dai, Chuan-Sheng Foo, See-Kiong Ng, Bryan Kian Hsiang Low
Annual Meeting of the Association for Computational Linguistics (ACL), Findings, 2025
arXiv / code / bibtex
Group-robust Sample Reweighting for Subpopulation Shifts via Influence Functions
Rui Qiao, Zhaoxuan Wu, Jingtan Wang, Pang Wei Koh, Bryan Kian Hsiang Low
International Conference on Learning Representations (ICLR), 2025
arXiv / code / bibtex
Rui Qiao, Zhaoxuan Wu, Jingtan Wang, Pang Wei Koh, Bryan Kian Hsiang Low
International Conference on Learning Representations (ICLR), 2025
arXiv / code / bibtex
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
Empirical Methods in Natural Language Processing Finding (EMNLP) Findings, 2024
arXiv / bibtex
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
Empirical Methods in Natural Language Processing Finding (EMNLP) Findings, 2024
arXiv / bibtex
Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions
Jingtan Wang*, Xiaoqiang Lin*, Rui Qiao*, Chuan-sheng Foo, Bryan Kian Hsiang Low
International Conference on Machine Learning (ICML), 2024
arXiv / code / bibtex
Jingtan Wang*, Xiaoqiang Lin*, Rui Qiao*, Chuan-sheng Foo, Bryan Kian Hsiang Low
International Conference on Machine Learning (ICML), 2024
arXiv / code / bibtex
Awards and Honors
Research Achievement Award, NUS, School of Computing, 2024; 2025.Dean’s List of Year 2018 – 2019; Dean’s List of Year 2020 – 2021, NTU, School of Computer Science and Engineering.
Senior Middle 2 Scholarship for top 1 percent student of China covered full tuition for undergraduate study.