Publications

Mohammadreza Pourreza, Shayan Talaei, Ruoxi Sun, Xingchen Wan, Hailong Li, Azalia Mirhoseini, Amin Saberi, Sercan Ö. Arık (2025). Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL. arXiv preprint arXiv:2503.23157.

PDF Cite Abstract

Xingchen Wan, Han Zhou, Ruoxi Sun, Hootan Nakhost, Ke Jiang, Sercan Ö. Arık (2025). From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation. International Conference on Learning Representations (ICLR).

PDF Cite Abstract

Han Zhou, Xingchen Wan, Ruoxi Sun, Hamid Palangi, Shariq Iqbal, Ivan Vulić, Anna Korhonen, Sercan Ö. Arık (2025). Multi-Agent Design: Optimizing Agents with Better Prompts and Topologies. arXiv preprint arXiv:2502.02533.

PDF Cite Abstract

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).

PDF Cite Abstract OpenReview

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).

PDF Cite Abstract OpenReview

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

PDF Cite Code Abstract OpenReview

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).

PDF Cite Code Abstract

Fei Wang, Xingchen Wan, Ruoxi Sun, Jiefeng Chen, Sercan Ö. Arık (2024). Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models. arXiv preprint arXiv:2410.07176.

PDF Cite Abstract

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).

PDF Cite Google Research Blog Abstract OpenReview

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).

PDF Cite Code Abstract

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

PDF Cite Code Abstract

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).

PDF Cite Code DOI Abstract

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).

PDF Cite Code Abstract

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).

PDF Cite Google Research Blog Abstract (Google Research) OpenReview ACL Anthology US Patent Slides & Talk

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.

PDF Cite Code Abstract OpenReview ACL Anthology

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).

PDF Cite Code Abstract OpenReview

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

PDF Cite Code OpenReview

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.

PDF Cite Google Research Blog Abstract (Google Research) ACL Anthology US Patent Slides & Talk

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).

PDF Cite Code Abstract (Meta Research) OpenReview Slides & Talk

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).

PDF Cite Code OpenReview Slides & Talk AutoML Seminars

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).

PDF Cite Code OpenReview Slides

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).

PDF Cite Code HTML

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).

PDF Cite Slides & Talk US Patent

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).

PDF Cite Code OpenReview Slides & Talk

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).

PDF Cite Code Slides & Talk

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).

PDF Cite Code OpenReview Slides & Talk

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.

PDF Cite Code HTML