MLRG Deep Curvature. - Diego Granziol; Xingchen Wan; Timur Garipov; Dmitry P. Vetrov; Stephen Roberts 001 (CoRR, 2019)

Iterate Averaging Helps: An Alternative Perspective in Deep Learning. - Diego Granziol; Xingchen Wan; Stephen Roberts 001 (CoRR, 2020)

Neural Architecture Search using Bayesian Optimisation with Weisfeiler-Lehman Kernel. - Bin Xin Ru; Xingchen Wan; Xiaowen Dong 001; Michael A. Osborne (CoRR, 2020)

Sentiment Diffusion in Financial News Networks and Associated Market Movements. - Xingchen Wan; Jie Yang; Slavi Marinov; Jan-Peter Calliess; Stefan Zohren; Xiaowen Dong 001 (CoRR, 2020)

Explaining the Adaptive Generalisation Gap. - Diego Granziol; Samuel Albanie; Xingchen Wan; Stephen J. Roberts (CoRR, 2020)

Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels. - Bin Xin Ru; Xingchen Wan; Xiaowen Dong 001; Michael A. Osborne (ICLR, 2021)

Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces. - Xingchen Wan; Vu Nguyen; Huong Ha 001; Bin Xin Ru; Cong Lu; Michael A. Osborne (ICML, 2021)

Adversarial Attacks on Graph Classifiers via Bayesian Optimisation. - Xingchen Wan; Henry Kenlay; Robin Ru; Arno Blaas; Michael A. Osborne; Xiaowen Dong 001 (NeurIPS, 2021)

Adversarial Attacks on Graph Classification via Bayesian Optimisation. - Xingchen Wan; Henry Kenlay; Binxin Ru; Arno Blaas; Michael A. Osborne; Xiaowen Dong 001 (CoRR, 2021)

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

BOiLS: Bayesian Optimisation for Logic Synthesis. - Antoine Grosnit; Cédric Malherbe; Rasul Tutunov; Xingchen Wan; Jun Wang 012; Haitham Bou-Ammar (DATE, 2022)

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

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

Approximate Neural Architecture Search via Operation Distribution Learning. - Xingchen Wan; Binxin Ru; Pedro M. Esperança; Fabio Maria Carlucci (WACV, 2022)

Estimation of Reference Voltages for Time-Difference Electrical Impedance Tomography. - Hao Yu; Xingchen Wan; Zhongxu Dong; Zhixi Zhang; Jiabin Jia (IEEE Trans. Instrum. Meas., 2022)

Better Zero-Shot Reasoning with Self-Adaptive Prompting. - Xingchen Wan; Ruoxi Sun 002; Hanjun Dai; Sercan Ö. Arik; Tomas Pfister (ACL (Findings), 2023)

Universal Self-Adaptive Prompting. - Xingchen Wan; Ruoxi Sun 002; Hootan Nakhost; Hanjun Dai; Julian Eisenschlos; Sercan Ö. Arik; Tomas Pfister (EMNLP, 2023)

Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning. - Han Zhou 010; Xingchen Wan; Ivan Vulic; Anna Korhonen (EMNLP (Findings), 2023)

Bayesian Optimisation of Functions on Graphs. - Xingchen Wan; Pierre Osselin; Henry Kenlay; Binxin Ru; Michael A. Osborne; Xiaowen Dong 001 (NeurIPS, 2023)

SimSC: A Simple Framework for Semantic Correspondence with Temperature Learning. - Xinghui Li; Kai Han 001; Xingchen Wan; Victor Adrian Prisacariu (CoRR, 2023)

Domain-Agnostic Batch Bayesian Optimization with Diverse Constraints via Bayesian Quadrature. - Masaki Adachi; Satoshi Hayakawa; Xingchen Wan; Martin Jørgensen; Harald Oberhauser; Michael A. Osborne (CoRR, 2023)

Bayesian Quadrature for Neural Ensemble Search. - Saad Hamid; Xingchen Wan; Martin Jørgensen; Binxin Ru; Michael A. Osborne (Trans. Mach. Learn. Res., 2023)

Working Memory Capacity of ChatGPT: An Empirical Study. - Dongyu Gong; Xingchen Wan; Dingmin Wang (AAAI, 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 (AISTATS, 2024)

Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments. - Han Zhou 010; Xingchen Wan; Yinhong Liu; Nigel Collier; Ivan Vulic; Anna Korhonen (EMNLP, 2024)

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering. - Han Zhou 010; Xingchen Wan; Lev Proleev; Diana Mincu; Jilin Chen; Katherine A. Heller; Subhrajit Roy (ICLR, 2024)

UQE: A Query Engine for Unstructured Databases. - Hanjun Dai; Bethany Wang; Xingchen Wan; Bo Dai 001; Sherry Yang 001; Azade Nova; Pengcheng Yin; Phitchaya Mangpo Phothilimthana; Charles Sutton; Dale Schuurmans (NeurIPS, 2024)

Bayesian Optimization of Functions over Node Subsets in Graphs. - Huidong Liang; Xingchen Wan; Xiaowen Dong 001 (NeurIPS, 2024)

Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization. - Xingchen Wan; Ruoxi Sun 002; Hootan Nakhost; Sercan Ö. Arik (NeurIPS, 2024)

Iterate Averaging in the Quest for Best Test Error. - Diego Granziol; Nicholas P. Baskerville; Xingchen Wan; Samuel Albanie; Stephen Roberts 001 (J. Mach. Learn. Res., 2024)

AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning. - Han Zhou 010; Xingchen Wan; Ivan Vulic; Anna Korhonen (Trans. Assoc. Comput. Linguistics, 2024)

Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models. - Fei Wang; Xingchen Wan; Ruoxi Sun 002; Jiefeng Chen 001; Sercan Ö. Arik (ACL (1), 2025)

From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation. - Xingchen Wan; Han Zhou 010; Ruoxi Sun 002; Sercan Ö. Arik (ICLR, 2025)

From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation. - Xingchen Wan; Han Zhou 010; Ruoxi Sun 002; Hootan Nakhost; Ke Jiang; Sercan Ö. Arik (CoRR, 2025)

Multi-Agent Design: Optimizing Agents with Better Prompts and Topologies. - Han Zhou 010; Xingchen Wan; Ruoxi Sun 002; Hamid Palangi; Shariq Iqbal; Ivan Vulic; Anna Korhonen; Sercan Ö. Arik (CoRR, 2025)

Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL. - Mohammadreza Pourreza; Shayan Talaei; Ruoxi Sun 002; Xingchen Wan; Hailong Li; Azalia Mirhoseini; Amin Saberi; Sercan Ö. Arik (CoRR, 2025)

Visual Planning: Let's Think Only with Images. - Yi Xu; Chengzu Li; Han Zhou 010; Xingchen Wan; Caiqi Zhang; Anna Korhonen; Ivan Vulic (CoRR, 2025)

DynScaling: Efficient Verifier-free Inference Scaling via Dynamic and Integrated Sampling. - Fei Wang; Xingchen Wan; Ruoxi Sun 002; Jiefeng Chen 001; Sercan Ö. Arik (CoRR, 2025)