Zhengying Liu

According to our database, Zhengying Liu authored at least 38 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Trans. Mach. Learn. Res., 2024

FormalAlign: Automated Alignment Evaluation for Autoformalization.

Jianqiao Lu, Yingjia Wan, Yinya Huang, Jing Xiong, Zhengying Liu, Zhijiang Guo

CoRR, 2024

ToolACE: Winning the Points of LLM Function Calling.

Weiwen Liu, Xu Huang, Xingshan Zeng, Xinlong Hao, Shuai Yu, Dexun Li, Shuai Wang, Weinan Gan, Zhengying Liu, Yuanqing Yu, Zezhong Wang, Yuxian Wang, Wu Ning, Yutai Hou, Bin Wang, Chuhan Wu, Xinzhi Wang, Yong Liu, Yasheng Wang, Duyu Tang, Dandan Tu, Lifeng Shang, Xin Jiang, Ruiming Tang, Defu Lian, Qun Liu, Enhong Chen

CoRR, 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

CoRR, 2024

Process-Driven Autoformalization in Lean 4.

Jianqiao Lu, Zhengying Liu, Yingjia Wan, Yinya Huang, Haiming Wang, Zhicheng Yang, Jing Tang, Zhijiang Guo

CoRR, 2024

Proving Theorems Recursively.

Haiming Wang, Huajian Xin, Zhengying Liu, Wenda Li, Yinya Huang, Jianqiao Lu, Zhicheng Yang, Jing Tang, Jian Yin, Zhenguo Li, Xiaodan Liang

CoRR, 2024

ATG: Benchmarking Automated Theorem Generation for Generative Language Models.

Xiaohan Lin, Qingxing Cao, Yinya Huang, Zhicheng Yang, Zhengying Liu, Zhenguo Li, Xiaodan Liang

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu

Proceedings of the Twelfth International Conference on Learning Representations, 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, Zhenguo Li, Xiaodan Liang

Proceedings of the Twelfth International Conference on Learning Representations, 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

Proceedings of the Twelfth International Conference on Learning Representations, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis.

Kai Chen, Chunwei Wang, Kuo Yang, Jianhua Han, Lanqing Hong, Fei Mi, Hang Xu, Zhengying Liu, Wenyong Huang, Zhenguo Li, Dit-Yan Yeung, Lifeng Shang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Forward-Backward Reasoning in Large Language Models for Mathematical Verification.

Weisen Jiang, Han Shi, Longhui Yu, Zhengying Liu, Yu Zhang, Zhenguo Li, James T. Kwok

Proceedings of the Findings of the Association for Computational Linguistics, 2024

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, Mengzhe Geng, Yue Wu, Wenhai Wang, Junsong Chen, Zhangyue Yin, Xiaozhe Ren, Jie Fu, Junxian He, Wu Yuan, Qi Liu, Xihui Liu, Yu Li, Hao Dong, Yu Cheng, Ming Zhang, Pheng-Ann Heng, Jifeng Dai, Ping Luo, Jingdong Wang, Ji-Rong Wen, Xipeng Qiu, Yike Guo, Hui Xiong, Qun Liu, Zhenguo Li

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

CoRR, 2023

Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis.

Kai Chen, Chunwei Wang, Kuo Yang, Jianhua Han, Lanqing Hong, Fei Mi, Hang Xu, Zhengying Liu, Wenyong Huang, Zhenguo Li, Dit-Yan Yeung, Lifeng Shang, Xin Jiang, Qun Liu

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, Zhenguo Li, Heng Liao, Xiaodan Liang

CoRR, 2023

FIMO: A Challenge Formal Dataset for Automated Theorem Proving.

Chengwu Liu, Jianhao Shen, Huajian Xin, Zhengying Liu, Ye Yuan, Haiming Wang, Wei Ju, Chuanyang Zheng, Yichun Yin, Lin Li, Ming Zhang, Qun Liu

CoRR, 2023

Forward-Backward Reasoning in Large Language Models for Verification.

Weisen Jiang, Han Shi, Longhui Yu, Zhengying Liu, Yu Zhang, Zhenguo Li, James T. Kwok

CoRR, 2023

Progressive-Hint Prompting Improves Reasoning in Large Language Models.

Chuanyang Zheng, Zhengying Liu, Enze Xie, Zhenguo Li, Yu Li

CoRR, 2023

TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models.

Jing Xiong, Jianhao Shen, Ye Yuan, Haiming Wang, Yichun Yin, Zhengying Liu, Lin Li, Zhijiang Guo, Qingxing Cao, Yinya Huang, Chuanyang Zheng, Xiaodan Liang, Ming Zhang, Qun Liu

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

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, Zhenguo Li, Xiaodan Liang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Learning to Prove Trigonometric Identities.

Zhou Liu, Yujun Li, Zhengying Liu, Lin Li, Zhenguo Li

CoRR, 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, Fabio Ferreira, Henry Gouk, Shell Hu, Frank Hutter, Zhengying Liu, Felix Mohr, Jan N. van Rijn, Xin Wang, Isabelle Guyon

CoRR, 2022

Filtering participants improves generalization in competitions and benchmarks.

Adrien Pavão, Isabelle Guyon, Zhengying Liu

Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021

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

Zhengying Liu

PhD thesis, 2021

Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019.

Zhengying Liu, Adrien Pavao, Zhen Xu, Sergio Escalera, Fabio Ferreira, Isabelle Guyon, Sirui Hong, Frank Hutter, Rongrong Ji, Júlio C. S. Jacques Júnior, Ge Li, Marius Lindauer, Zhipeng Luo, Meysam Madadi, Thomas Nierhoff, Kangning Niu, Chunguang Pan, Danny Stoll, Sébastien Treguer, Jin Wang, Peng Wang, Chenglin Wu, Youcheng Xiong, Arber Zela, Yang Zhang

IEEE Trans. Pattern Anal. Mach. Intell., 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

Proceedings of the International Conference for High Performance Computing, 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, Fabio Ferreira, Henry Gouk, Chaoyu Guan, Isabelle Guyon, Timothy M. Hospedales, Shell Hu, Mike Huisman, Frank Hutter, Zhengying Liu, Felix Mohr, Ekrem Öztürk, Jan N. van Rijn, Haozhe Sun, Xin Wang, Wenwu Zhu

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Asymptotic Analysis of Meta-learning as a Recommendation Problem.

Zhengying Liu, Isabelle Guyon

Proceedings of the AAAI Workshop on Meta-Learning and MetaDL Challenge, 2021

Advances in MetaDL: AAAI 2021 Challenge and Workshop.

Adrian El Baz, Isabelle Guyon, Zhengying Liu, Jan N. van Rijn, Sébastien Treguer, Joaquin Vanschoren

Proceedings of the AAAI Workshop on Meta-Learning and MetaDL Challenge, 2021

2020

Towards automated computer vision: analysis of the AutoCV challenges 2019.

Zhengying Liu, Zhen Xu, Sergio Escalera, Isabelle Guyon, Júlio C. S. Jacques Júnior, Meysam Madadi, Adrien Pavao, Sébastien Treguer, Wei-Wei Tu

Pattern Recognit. Lett., 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

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

Deep Statistical Solvers.

Balthazar Donon, Zhengying Liu, Wenzhuo Liu, Isabelle Guyon, Antoine Marot, Marc Schoenauer

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019.

Zhengying Liu, Zhen Xu, Shangeth Rajaa, Meysam Madadi, Júlio C. S. Jacques Júnior, Sergio Escalera, Adrien Pavao, Sébastien Treguer, Wei-Wei Tu, Isabelle Guyon

Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019

LEAP nets for power grid perturbations.

Benjamin Donnot, Balthazar Donon, Isabelle Guyon, Zhengying Liu, Antoine Marot, Patrick Panciatici, Marc Schoenauer

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

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, Evelyne Viegas

Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019