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2020 – today
- 2024
[j4]Chuanyang Zheng, Haiming Wang, Enze Xie, Zhengying Liu, Jiankai Sun, Huajian Xin, Jianhao Shen, Zhenguo Li, Yu Li:
Lyra: Orchestrating Dual Correction in Automated Theorem Proving. Trans. Mach. Learn. Res. 2024 (2024)- [c17]Weisen Jiang, Han Shi, Longhui Yu, Zhengying Liu, Yu Zhang, Zhenguo Li, James T. Kwok:
Forward-Backward Reasoning in Large Language Models for Mathematical Verification. ACL (Findings) 2024: 6647-6661 - [c16]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:
Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis. ICLR 2024 - [c15]Yinya Huang, Xiaohan Lin, Zhengying Liu, Qingxing Cao, Huajian Xin, Haiming Wang, Zhenguo Li, Linqi Song, Xiaodan Liang:
MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data. ICLR 2024 - [c14]Yuanfeng Ji, Chongjian Ge, Weikai Kong, Enze Xie, Zhengying Liu, Zhenguo Li, Ping Luo:
Large Language Models as Automated Aligners for benchmarking Vision-Language Models. ICLR 2024 - [c13]Haiming Wang, Huajian Xin, Chuanyang Zheng, Zhengying Liu, Qingxing Cao, Yinya Huang, Jing Xiong, Han Shi, Enze Xie, Jian Yin, Zhenguo Li, Xiaodan Liang:
LEGO-Prover: Neural Theorem Proving with Growing Libraries. ICLR 2024 - [c12]Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu:
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models. ICLR 2024 - [c11]Xiaohan Lin, Qingxing Cao, Yinya Huang, Zhicheng Yang, Zhengying Liu, Zhenguo Li, Xiaodan Liang:
ATG: Benchmarking Automated Theorem Generation for Generative Language Models. NAACL-HLT (Findings) 2024: 4465-4480 - [i23]Yinya Huang, Xiaohan Lin, Zhengying Liu, Qingxing Cao, Huajian Xin, Haiming Wang, Zhenguo Li, Linqi Song, Xiaodan Liang:
MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data. CoRR abs/2402.08957 (2024) - [i22]Xiaohan Lin, Qingxing Cao, Yinya Huang, Zhicheng Yang, Zhengying Liu, Zhenguo Li, Xiaodan Liang:
ATG: Benchmarking Automated Theorem Generation for Generative Language Models. CoRR abs/2405.06677 (2024) - [i21]Haiming Wang, Huajian Xin, Zhengying Liu, Wenda Li, Yinya Huang, Jianqiao Lu, Zhicheng Yang, Jing Tang, Jian Yin, Zhenguo Li, Xiaodan Liang:
Proving Theorems Recursively. CoRR abs/2405.14414 (2024) - [i20]Jianqiao Lu, Zhengying Liu, Yingjia Wan, Yinya Huang, Haiming Wang, Zhicheng Yang, Jing Tang, Zhijiang Guo:
Process-Driven Autoformalization in Lean 4. CoRR abs/2406.01940 (2024) - [i19]Xiaohan Lin, Qingxing Cao, Yinya Huang, Haiming Wang, Jianqiao Lu, Zhengying Liu, Linqi Song, Xiaodan Liang:
FVEL: Interactive Formal Verification Environment with Large Language Models via Theorem Proving. CoRR abs/2406.14408 (2024) - [i18]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:
ToolACE: Winning the Points of LLM Function Calling. CoRR abs/2409.00920 (2024) - [i17]Jianqiao Lu, Yingjia Wan, Yinya Huang, Jing Xiong, Zhengying Liu, Zhijiang Guo:
FormalAlign: Automated Alignment Evaluation for Autoformalization. CoRR abs/2410.10135 (2024) - 2023
- [c10]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:
DT-Solver: Automated Theorem Proving with Dynamic-Tree Sampling Guided by Proof-level Value Function. ACL (1) 2023: 12632-12646 - [c9]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:
TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models. EMNLP 2023: 11594-11632 - [i16]Chuanyang Zheng, Zhengying Liu, Enze Xie, Zhenguo Li, Yu Li:
Progressive-Hint Prompting Improves Reasoning in Large Language Models. CoRR abs/2304.09797 (2023) - [i15]Weisen Jiang, Han Shi, Longhui Yu, Zhengying Liu, Yu Zhang, Zhenguo Li, James T. Kwok:
Forward-Backward Reasoning in Large Language Models for Verification. CoRR abs/2308.07758 (2023) - [i14]Chengwu Liu, Jianhao Shen, Huajian Xin, Zhengying Liu, Ye Yuan, Haiming Wang, Wei Ju, Chuanyang Zheng, Yichun Yin, Lin Li, Ming Zhang, Qun Liu:
FIMO: A Challenge Formal Dataset for Automated Theorem Proving. CoRR abs/2309.04295 (2023) - [i13]Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu:
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models. CoRR abs/2309.12284 (2023) - [i12]Chuanyang Zheng, Haiming Wang, Enze Xie, Zhengying Liu, Jiankai Sun, Huajian Xin, Jianhao Shen, Zhenguo Li, Yu Li:
Lyra: Orchestrating Dual Correction in Automated Theorem Proving. CoRR abs/2309.15806 (2023) - [i11]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:
LEGO-Prover: Neural Theorem Proving with Growing Libraries. CoRR abs/2310.00656 (2023) - [i10]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:
TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models. CoRR abs/2310.10180 (2023) - [i9]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:
Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis. CoRR abs/2310.10477 (2023) - [i8]Yuanfeng Ji, Chongjian Ge, Weikai Kong, Enze Xie, Zhengying Liu, Zhengguo Li, Ping Luo:
Large Language Models as Automated Aligners for benchmarking Vision-Language Models. CoRR abs/2311.14580 (2023) - [i7]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:
A Survey of Reasoning with Foundation Models. CoRR abs/2312.11562 (2023) - 2022
- [c8]Adrien Pavão, Isabelle Guyon, Zhengying Liu:
Filtering participants improves generalization in competitions and benchmarks. ESANN 2022 - [i6]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:
Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019. CoRR abs/2201.03801 (2022) - [i5]Adrian El Baz, Isabelle Guyon, Zhengying Liu, Jan N. van Rijn, Sébastien Treguer, Joaquin Vanschoren:
Advances in MetaDL: AAAI 2021 challenge and workshop. CoRR abs/2202.01890 (2022) - [i4]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:
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. CoRR abs/2206.08138 (2022) - [i3]Zhou Liu, Yujun Li, Zhengying Liu, Lin Li, Zhenguo Li:
Learning to Prove Trigonometric Identities. CoRR abs/2207.06679 (2022) - 2021
- [b1]Zhengying Liu:
Automated Deep Learning : Principles and Practice. (Apprentissage profond automatisé : principes et pratique). University of Paris-Saclay, France, 2021 - [j3]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:
Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019. IEEE Trans. Pattern Anal. Mach. Intell. 43(9): 3108-3125 (2021) - [c7]Adrian El Baz, Isabelle Guyon, Zhengying Liu, Jan N. van Rijn, Sébastien Treguer, Joaquin Vanschoren:
Advances in MetaDL: AAAI 2021 Challenge and Workshop. MetaDL@AAAI 2021: 1-16 - [c6]Zhengying Liu, Isabelle Guyon:
Asymptotic Analysis of Meta-learning as a Recommendation Problem. MetaDL@AAAI 2021: 100-114 - [c5]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:
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. NeurIPS (Competition and Demos) 2021: 80-96 - [c4]Romain Égelé, Prasanna Balaprakash, Isabelle Guyon, Venkatram Vishwanath, Fangfang Xia, Rick Stevens, Zhengying Liu:
AgEBO-tabular: joint neural architecture and hyperparameter search with autotuned data-parallel training for tabular data. SC 2021: 30 - 2020
- [j2]Balthazar Donon, Benjamin Donnot, Isabelle Guyon, Zhengying Liu, Antoine Marot, Patrick Panciatici, Marc Schoenauer:
LEAP nets for system identification and application to power systems. Neurocomputing 416: 316-327 (2020) - [j1]Zhengying Liu, Zhen Xu, Sergio Escalera, Isabelle Guyon, Júlio C. S. Jacques Júnior, Meysam Madadi, Adrien Pavao, Sébastien Treguer, Wei-Wei Tu:
Towards automated computer vision: analysis of the AutoCV challenges 2019. Pattern Recognit. Lett. 135: 196-203 (2020) - [c3]Balthazar Donon, Zhengying Liu, Wenzhuo Liu, Isabelle Guyon, Antoine Marot, Marc Schoenauer:
Deep Statistical Solvers. NeurIPS 2020 - [i2]Romain Egele, Prasanna Balaprakash, Venkatram Vishwanath, Isabelle Guyon, Zhengying Liu:
AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data. CoRR abs/2010.16358 (2020)
2010 – 2019
- 2019
- [c2]Benjamin Donnot, Balthazar Donon, Isabelle Guyon, Zhengying Liu, Antoine Marot, Patrick Panciatici, Marc Schoenauer:
LEAP nets for power grid perturbations. ESANN 2019 - [c1]Zhengying Liu, Zhen Xu, Shangeth Rajaa, Meysam Madadi, Júlio C. S. Jacques Júnior, Sergio Escalera, Adrien Pavao, Sébastien Treguer, Wei-Wei Tu, Isabelle Guyon:
Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019. NeurIPS (Competition and Demos) 2019: 242-252 - [p1]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:
Analysis of the AutoML Challenge Series 2015-2018. Automated Machine Learning 2019: 177-219 - [i1]Benjamin Donnot, Balthazar Donon, Isabelle Guyon, Zhengying Liu, Antoine Marot, Patrick Panciatici, Marc Schoenauer:
LEAP nets for power grid perturbations. CoRR abs/1908.08314 (2019)
Coauthor Index
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