Wan, Xingchen

20 publications

ICLR 2025 From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation Xingchen Wan, Han Zhou, Ruoxi Sun, Sercan O Arik

AISTATS 2024 Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne

ICLR 2024 Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen, Katherine A Heller, Subhrajit Roy

NeurIPS 2024 Bayesian Optimization of Functions over Node Subsets in Graphs Huidong Liang, Xingchen Wan, Xiaowen Dong

JMLR 2024 Iterate Averaging in the Quest for Best Test Error Diego Granziol, Nicholas P. Baskerville, Xingchen Wan, Samuel Albanie, Stephen Roberts

NeurIPS 2024 Teach Better or Show Smarter? on Instructions and Exemplars in Automatic Prompt Optimization Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Sercan Ö. Arık

NeurIPS 2024 UQE: A Query Engine for Unstructured Databases Hanjun Dai, Bethany Yixin Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans

AAAI 2024 Working Memory Capacity of ChatGPT: An Empirical Study Dongyu Gong, Xingchen Wan, Dingmin Wang

NeurIPSW 2023 Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen, Katherine Heller, Subhrajit Roy

NeurIPS 2023 Bayesian Optimisation of Functions on Graphs Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A Osborne, Xiaowen Dong

TMLR 2023 Bayesian Quadrature for Neural Ensemble Search Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A Osborne

WACV 2022 Approximate Neural Architecture Search via Operation Distribution Learning Xingchen Wan, Binxin Ru, Pedro M. Esparança, Fabio Maria Carlucci

AutoML 2022 Bayesian Generational Population-Based Training Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael Osborne

ICLRW 2022 Bayesian Generational Population-Based Training Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael Osborne

NeurIPS 2022 Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A Osborne, Eytan Bakshy

ICLR 2022 On Redundancy and Diversity in Cell-Based Neural Architecture Search Xingchen Wan, Binxin Ru, Pedro M Esperança, Zhenguo Li

NeurIPS 2021 Adversarial Attacks on Graph Classifiers via Bayesian Optimisation Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A Osborne, Xiaowen Dong

ICMLW 2021 Attacking Graph Classification via Bayesian Optimisation Xingchen Wan, Henry Kenlay, Binxin Ru, Arno Blaas, Michael Osborne, Xiaowen Dong

ICLR 2021 Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels Binxin Ru, Xingchen Wan, Xiaowen Dong, Michael Osborne

ICML 2021 Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces Xingchen Wan, Vu Nguyen, Huong Ha, Binxin Ru, Cong Lu, Michael A. Osborne