Analysis of the AutoML Challenge Series 2015-2018. - Isabelle Guyon; Lisheng Sun-Hosoya; Marc Boullé; Hugo Jair Escalante; Sergio Escalera; Zhengying Liu; Damir Jajetic; Bisakha Ray; Mehreen Saeed; Michèle Sebag; Alexander R. Statnikov; Wei-Wei Tu; et al. (Automated Machine Learning, 2019)

LEAP nets for power grid perturbations. - Benjamin Donnot; Balthazar Donon; Isabelle Guyon; Zhengying Liu; Antoine Marot; Patrick Panciatici; Marc Schoenauer (ESANN, 2019)

Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019. - Zhengying Liu; Zhen Xu 007; Shangeth Rajaa; Meysam Madadi; Júlio C. S. Jacques Júnior; Sergio Escalera; Adrien Pavao; Sébastien Treguer; Wei-Wei Tu; Isabelle Guyon (NeurIPS (Competition and Demos), 2019)

Deep Statistical Solvers. - Balthazar Donon; Zhengying Liu; Wenzhuo Liu; Isabelle Guyon; Antoine Marot; Marc Schoenauer (NeurIPS, 2020)

AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data. - Romain Egele; Prasanna Balaprakash; Venkatram Vishwanath; Isabelle Guyon; Zhengying Liu (CoRR, 2020)

LEAP nets for system identification and application to power systems. - Balthazar Donon; Benjamin Donnot; Isabelle Guyon; Zhengying Liu; Antoine Marot; Patrick Panciatici; Marc Schoenauer (Neurocomputing, 2020)

Towards automated computer vision: analysis of the AutoCV challenges 2019. - Zhengying Liu; Zhen Xu 007; Sergio Escalera; Isabelle Guyon; Júlio C. S. Jacques Júnior; Meysam Madadi; Adrien Pavao; Sébastien Treguer; Wei-Wei Tu (Pattern Recognit. Lett., 2020)

Advances in MetaDL: AAAI 2021 Challenge and Workshop. - Adrian El Baz; Isabelle Guyon; Zhengying Liu; Jan N. van Rijn; Sébastien Treguer; Joaquin Vanschoren (MetaDL@AAAI, 2021)

Asymptotic Analysis of Meta-learning as a Recommendation Problem. - Zhengying Liu; Isabelle Guyon (MetaDL@AAAI, 2021)

Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. - Adrian El Baz; Ihsan Ullah; Edesio Alcobaça; André C. P. L. F. de Carvalho; Hong Chen 011; Fabio Ferreira; Henry Gouk; Chaoyu Guan; Isabelle Guyon; Timothy M. Hospedales; Shell Hu; Mike Huisman; et al. (NeurIPS (Competition and Demos), 2021)

AgEBO-tabular: joint neural architecture and hyperparameter search with autotuned data-parallel training for tabular data. - Romain Égelé; Prasanna Balaprakash; Isabelle Guyon; Venkatram Vishwanath; Fangfang Xia; Rick Stevens; Zhengying Liu (SC, 2021)

Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019. - Zhengying Liu; Adrien Pavao; Zhen Xu 007; Sergio Escalera; Fabio Ferreira; Isabelle Guyon; Sirui Hong; Frank Hutter; Rongrong Ji; Júlio C. S. Jacques Júnior; Ge Li; Marius Lindauer; et al. (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Automated Deep Learning : Principles and Practice. (Apprentissage profond automatisé : principes et pratique). - Zhengying Liu (2021)

Filtering participants improves generalization in competitions and benchmarks. - Adrien Pavão; Isabelle Guyon; Zhengying Liu (ESANN, 2022)

Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. - Adrian El Baz; André C. P. L. F. de Carvalho; Hong Chen 011; Fabio Ferreira; Henry Gouk; Shell Hu; Frank Hutter; Zhengying Liu; Felix Mohr; Jan N. van Rijn; Xin Wang 019; Isabelle Guyon (CoRR, 2022)

Learning to Prove Trigonometric Identities. - Zhou Liu; Yujun Li; Zhengying Liu; Lin Li; Zhenguo Li (CoRR, 2022)

DT-Solver: Automated Theorem Proving with Dynamic-Tree Sampling Guided by Proof-level Value Function. - Haiming Wang; Ye Yuan; Zhengying Liu; Jianhao Shen; Yichun Yin; Jing Xiong; Enze Xie; Han Shi; Yujun Li; Lin Li; Jian Yin 001; Zhenguo Li; et al. (ACL (1), 2023)

TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models. - Jing Xiong; Jianhao Shen; Ye Yuan 016; Haiming Wang; Yichun Yin; Zhengying Liu; Lin Li; Zhijiang Guo; Qingxing Cao; Yinya Huang; Chuanyang Zheng; Xiaodan Liang; et al. (EMNLP, 2023)

Progressive-Hint Prompting Improves Reasoning in Large Language Models. - Chuanyang Zheng; Zhengying Liu; Enze Xie; Zhenguo Li; Yu Li (CoRR, 2023)

Forward-Backward Reasoning in Large Language Models for Verification. - Weisen Jiang; Han Shi; Longhui Yu; Zhengying Liu; Yu Zhang 006; Zhenguo Li; James T. Kwok (CoRR, 2023)

FIMO: A Challenge Formal Dataset for Automated Theorem Proving. - Chengwu Liu 001; Jianhao Shen; Huajian Xin; Zhengying Liu; Ye Yuan 016; Haiming Wang; Wei Ju 001; Chuanyang Zheng; Yichun Yin; Lin Li; Ming Zhang 004; Qun Liu 001 (CoRR, 2023)

LEGO-Prover: Neural Theorem Proving with Growing Libraries. - Haiming Wang; Huajian Xin; Chuanyang Zheng; Lin Li; Zhengying Liu; Qingxing Cao; Yinya Huang; Jing Xiong; Han Shi; Enze Xie; Jian Yin 001; Zhenguo Li; et al. (CoRR, 2023)

Large Language Models as Automated Aligners for benchmarking Vision-Language Models. - Yuanfeng Ji; Chongjian Ge; Weikai Kong; Enze Xie; Zhengying Liu; Zhengguo Li; Ping Luo 002 (CoRR, 2023)

A Survey of Reasoning with Foundation Models. - Jiankai Sun; Chuanyang Zheng; Enze Xie; Zhengying Liu; Ruihang Chu; Jianing Qiu; Jiaqi Xu; Mingyu Ding; Hongyang Li 001; Mengzhe Geng; Yue Wu 002; Wenhai Wang; et al. (CoRR, 2023)

Forward-Backward Reasoning in Large Language Models for Mathematical Verification. - Weisen Jiang; Han Shi; Longhui Yu; Zhengying Liu; Yu Zhang 006; Zhenguo Li; James T. Kwok (ACL (Findings), 2024)

Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis. - Kai Chen 023; Chunwei Wang; Kuo Yang; Jianhua Han; Lanqing Hong; Fei Mi; Hang Xu 004; Zhengying Liu; Wenyong Huang; Zhenguo Li; Dit-Yan Yeung; Lifeng Shang; et al. (ICLR, 2024)

MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data. - Yinya Huang; Xiaohan Lin; Zhengying Liu; Qingxing Cao; Huajian Xin; Haiming Wang; Zhenguo Li; Linqi Song; Xiaodan Liang (ICLR, 2024)

Large Language Models as Automated Aligners for benchmarking Vision-Language Models. - Yuanfeng Ji; Chongjian Ge; Weikai Kong; Enze Xie; Zhengying Liu; Zhenguo Li; Ping Luo 002 (ICLR, 2024)

LEGO-Prover: Neural Theorem Proving with Growing Libraries. - Haiming Wang; Huajian Xin; Chuanyang Zheng; Zhengying Liu; Qingxing Cao; Yinya Huang; Jing Xiong; Han Shi; Enze Xie; Jian Yin 001; Zhenguo Li; Xiaodan Liang (ICLR, 2024)

MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models. - Longhui Yu; Weisen Jiang; Han Shi; Jincheng Yu; Zhengying Liu; Yu Zhang 006; James T. Kwok; Zhenguo Li; Adrian Weller; Weiyang Liu (ICLR, 2024)

ATG: Benchmarking Automated Theorem Generation for Generative Language Models. - Xiaohan Lin; Qingxing Cao; Yinya Huang; Zhicheng Yang; Zhengying Liu; Zhenguo Li; Xiaodan Liang (NAACL-HLT (Findings), 2024)

FVEL: Interactive Formal Verification Environment with Large Language Models via Theorem Proving. - Xiaohan Lin; Qingxing Cao; Yinya Huang; Haiming Wang; Jianqiao Lu; Zhengying Liu; Linqi Song; Xiaodan Liang (NeurIPS, 2024)

Proving Theorems Recursively. - Haiming Wang; Huajian Xin; Zhengying Liu; Wenda Li; Yinya Huang; Jianqiao Lu; Zhicheng Yang; Jing Tang 004; Jian Yin 001; Zhenguo Li; Xiaodan Liang (NeurIPS, 2024)

Process-Driven Autoformalization in Lean 4. - Jianqiao Lu; Zhengying Liu; Yingjia Wan; Yinya Huang; Haiming Wang; Zhicheng Yang; Jing Tang 004; Zhijiang Guo (CoRR, 2024)

Lyra: Orchestrating Dual Correction in Automated Theorem Proving. - Chuanyang Zheng; Haiming Wang; Enze Xie; Zhengying Liu; Jiankai Sun; Huajian Xin; Jianhao Shen; Zhenguo Li; Yu Li 006 (Trans. Mach. Learn. Res., 2024)

ToolACE: Winning the Points of LLM Function Calling. - Weiwen Liu; Xu Huang 008; Xingshan Zeng; Xinlong Hao; Shuai Yu; Dexun Li; Shuai Wang 020; Weinan Gan; Zhengying Liu; Yuanqing Yu; Zezhong Wang 004; Yuxian Wang; et al. (ICLR, 2025)

FormalAlign: Automated Alignment Evaluation for Autoformalization. - Jianqiao Lu; Yingjia Wan; Yinya Huang; Jing Xiong; Zhengying Liu; Zhijiang Guo (ICLR, 2025)

Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning. - Haiming Wang; Mert Unsal; Xiaohan Lin; Mantas Baksys; Junqi Liu; Marco Dos Santos; Flood Sung; Marina Vinyes; Zhenzhe Ying; Zekai Zhu; Jianqiao Lu; Hugues de Saxcé; et al. (CoRR, 2025)

Kimina Lean Server: Technical Report. - Marco Dos Santos; Haiming Wang; Hugues de Saxcé; Ran Wang; Mantas Baksys; Mert Unsal; Junqi Liu; Zhengying Liu; Jia Li (CoRR, 2025)

CombiBench: Benchmarking LLM Capability for Combinatorial Mathematics. - Junqi Liu; Xiaohan Lin; Jonas Bayer; Yael Dillies; Weijie Jiang; Xiaodan Liang; Roman Soletskyi; Haiming Wang; Yunzhou Xie; Beibei Xiong; Zhengfeng Yang; Jujian Zhang; et al. (CoRR, 2025)

Uncovering human behavioral heterogeneity in urban mobility under the impacts of disruptive weather events. - Zhaoya Gong; Zhicheng Deng; Junqing Tang; Hongbo Zhao; Zhengying Liu; Pengjun Zhao (Int. J. Geogr. Inf. Sci., 2025)

Kimi K2: Open Agentic Intelligence. - Yifan Bai; Yiping Bao; Guanduo Chen; Jiahao Chen; Ningxin Chen; Ruijue Chen; Yanru Chen; Yuankun Chen; Yutian Chen; Zhuofu Chen; Jialei Cui; Hao Ding; et al. (CoRR, 2025)

LeanGeo: Formalizing Competitional Geometry problems in Lean. - Chendong Song; Zihan Wang; Frederick Pu; Haiming Wang; Xiaohan Lin; Junqi Liu; Jia Li; Zhengying Liu (CoRR, 2025)

A Survey of Reasoning with Foundation Models: Concepts, Methodologies, and Outlook. - Jiankai Sun; Chuanyang Zheng; Enze Xie; Zhengying Liu; Ruihang Chu; Jianing Qiu; Jiaqi Xu; Mingyu Ding; Hongyang Li 001; Mengzhe Geng; Yue Wu 012; Wenhai Wang; et al. (ACM Comput. Surv., 2025)