Publications

Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Sercan Ö. Arık (2024). Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization. Advances in Neural Information Processing Systems (NeurIPS).

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Hanjun Dai, Bethany Yixin Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans (2024). UQE: A Query Engine for Unstructured Databases. Advances in Neural Information Processing Systems (NeurIPS).

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Huidong Liang, Xingchen Wan, Xiaowen Dong (2024). Bayesian Optimization of Functions over Node Subsets in Graphs. Advances in Neural Information Processing Systems (NeurIPS).

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Han Zhou, Xingchen Wan, Yinhong Liu, Nigel Collier, Ivan Vulić, Anna Korhonen (2024). Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments. Empirical Methods in Natural Language Processing (EMNLP).

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Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen, Katherine Heller, Subhrajit Roy (2024). Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering. International Conference on Learning Representations (ICLR).

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Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael Osborne (2024). Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach. International Conference on Artificial Intelligence and Statistics (AISTATS).

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Dongyu Gong, Xingchen Wan, Dingmin Wang (2024). Working Memory Capacity of ChatGPT: An Empirical Study. AAAI Conference on Artificial Intelligence (AAAI).

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Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen (2024). AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning. Transactions of the Association for Computational Linguistics (TACL).

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Diego Granziol, Nick P. Baskerville, Xingchen Wan, Samuel Albanie, Stephen Roberts (2024). Iterate Averaging in the Quest for Best Test Error. Journal of Machine Learning Research (JMLR).

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Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Martin Eisenschlos, Sercan Ö. Arık, Tomas Pfister (2023). Universal Self-Adaptive Prompting. Empirical Methods in Natural Language Processing (EMNLP).

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Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen (2023). Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning. Findings of the Association for Computational Linguistics: EMNLP 2023.

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Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael Osborne, Xiaowen Dong (2023). Bayesian Optimisation of Functions on Graphs. Advances in Neural Information Processing Systems (NeurIPS).

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Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael Osborne (2023). Bayesian Quadrature for Neural Ensemble Search. Transactions on Machine Learning Research (TMLR).

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Xingchen Wan, Ruoxi Sun, Hanjun Dai, Sercan Ö. Arık, Tomas Pfister (2023). Better Zero-Shot Reasoning with Self-Adaptive Prompting. Findings of the Association for Computational Linguistics: ACL 2023.

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Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael Osborne, Eytan Bakshy (2022). Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization. Advances in Neural Information Processing Systems (NeurIPS).

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Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael Osborne (2022). Bayesian Generational Population-Based Training. International Conference on Automated Machine Learning (AutoML-Conf).

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Xingchen Wan, Binxin Ru, Pedro M. Esperança, Zhenguo Li (2022). On Redundancy and Diversity in Cell-based Neural Architecture Search. International Conference on Learning Representations (ICLR).

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Antoine Grosnit, Cedric Malherbe, Rasul Tutunov, Xingchen Wan, Jun Wang, Haitham Bou Ammar (2022). BOiLS: Bayesian Optimisation for Logic Synthesis. Design, Automation and Test in Europe (DATE).

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Xingchen Wan, Binxin Ru, Pedro M. Esperança, Fabio M. Carlucci (2022). Approximate Neural Architecture Search via Operation Distribution Learning. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

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Xingchen Wan, Henry Kenlay, Binxin Ru, Arno Blaas, Michael Osborne, Xiaowen Dong (2021). Adversarial Attacks on Graph Classifiers via Bayesian Optimisation. Advances in Neural Information Processing Systems (NeurIPS).

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

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Binxin Ru, Xingchen Wan, Xiaowen Dong, Michael Osborne (2021). Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels. International Conference on Learning Representations (ICLR).

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Xingchen Wan, Jie Yang, Slavi Marinov, Jan-Peter Calliess, Stefan Zohren, Xiaowen Dong (2021). Sentiment Correlation in Financial News Networks and Associated Market Movements. Scientific Reports 11.

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