Thank you for visiting my website!

I’m a final-year PhD candidate in the Data Mining Group at UIUC, where I’m fortunate to be advised by Prof. Jiawei Han. During my PhD, I have interned with Google DeepMind, the Llama 3 Post-Training Team at Meta, Microsoft Azure AI, and Microsoft Research. Generously supported by the Amazon PhD Fellowship, my research centers on the frontier evaluation and alignment of LLMs.

Papers

(* stands for equal contribution.)

2025

• Vibe Checker: Aligning Code Evaluation with Human Preference
  Ming Zhong, Xiang Zhou, Ting-Yun Chang, Qingze Wang, Nan Xu, Xiance Si, Dan Garrette, Shyam Upadhyay, Jeremiah Liu, Jiawei Han, Benoit Schillings, Jiao Sun
  Preprint    [ Paper ]
• POLARIS: A Post-Training Recipe for Scaling Reinforcement Learning on Advanced Reasoning Models
  Chenxin An, Zhihui Xie, Xiaonan Li, Lei Li, Jun Zhang, Shansan Gong, Ming Zhong, Jingjing Xu, Xipeng Qiu, Mingxuan Wang, Lingpeng Kong
  Preprint    [ Project Page | Code | Models ]
• Preference Leakage: A Contamination Problem in LLM-as-a-Judge
  Dawei Li, Renliang Sun, Yue Huang, Ming Zhong, Bohan Jiang, Jiawei Han, Xiangliang Zhang, Wei Wang, Huan Liu
  Best Paper Award, DIG-BUGS Workshop at ICML 2025    [ Paper | Code ]
• Law of the Weakest Link: Cross Capabilities of Large Language Models
  Ming Zhong*, Aston Zhang*, Xuewei Wang, Rui Hou, Wenhan Xiong, Chenguang Zhu, Zhengxing Chen, Liang Tan, Chloe Bi, Mike Lewis, Sravya Popuri, Sharan Narang, Melanie Kambadur, Dhruv Mahajan, Sergey Edunov, Jiawei Han, Laurens van der Maaten
  ICLR 2025    [ Paper | Code | Dataset | Project Page ]
• Why Does the Effective Context Length of LLMs Fall Short?
  Chenxin An, Jun Zhang, Ming Zhong, Lei Li, Shansan Gong, Yao Luo, Jingjing Xu, Lingpeng Kong
  ICLR 2025    [ Paper | Code ]

2024

• Multi-LoRA Composition for Image Generation
  Ming Zhong, Yelong Shen, Shuohang Wang, Yadong Lu, Yizhu Jiao, Siru Ouyang, Donghan Yu, Jiawei Han, Weizhu Chen
  TMLR    [ Paper | Code | Project Page ]
• Temperature-Centric Investigation of Speculative Decoding with Knowledge Distillation
  Siru Ouyang, Shuohang Wang, Minhao Jiang, Ming Zhong, Donghan Yu, Jiawei Han, Yelong Shen
  EMNLP 2024 Findings    [ Paper | Code ]
• See What LLMs Cannot Answer: A Self-Challenge Framework for Uncovering LLM Weaknesses
  Yulong Chen, Yang Liu, Jianhao Yan, Xuefeng Bai, Ming Zhong, Yinghao Yang, Ziyi Yang, Chenguang Zhu, Yue Zhang
  COLM 2024    [ Paper | Code ]
• Investigating Instruction Tuning Large Language Models on Graphs
  Kerui Zhu, Bo-Wei Huang, Bowen Jin, Yizhu Jiao, Ming Zhong, Kevin Chang, Shou-De Lin, Jiawei Han
  COLM 2024    [ Paper | Code ]
• L-Eval: Instituting Standardized Evaluation for Long Context Language Models
  Chenxin An, Shansan Gong, Ming Zhong, Xingjian Zhao, Mukai Li, Jun Zhang, Lingpeng Kong, Xipeng Qiu
  Outstanding Paper Award, ACL 2024    [ Paper | Code ]
• ActionIE: Action Extraction from Scientific Literature with Programming Languages
  Xianrui Zhong, Yufeng Du, Siru Ouyang, Ming Zhong, Tingfeng Luo, Qirong Ho, Hao Peng, Heng Ji, Jiawei Han
  ACL 2024    [ Paper | Code ]
• Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective
  Ming Zhong, Chenxin An, Weizhu Chen, Jiawei Han, Pengcheng He
  ICLR 2024    [ Paper | Code | Project Page ]
• Investigating Data Contamination for Pre-training Language Models
  Minhao Jiang, Ken Ziyu Liu, Ming Zhong, Rylan Schaeffer, Siru Ouyang, Jiawei Han, Sanmi Koyejo
  Best Paper Award, DPFM Workshop at ICLR 2024    [ Paper | Code ]

2023

• Dynosaur: a Dynamic Growth Paradigm for Instruction-Tuning Data Curation
  Da Yin*, Xiao Liu*, Fan Yin*, Ming Zhong*, Hritik Bansal, Jiawei Han, Kai-Wei Chang
  EMNLP 2023    [ Paper | Code | Project Page ]
• Instruct and Extract: Instruction Tuning for On-Demand Information Extraction
  Yizhu Jiao, Ming Zhong, Sha Li, Ruining Zhao, Siru Ouyang, Heng Ji, Jiawei Han
  EMNLP 2023 (Oral)    [ Paper | Code ]
• The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions
  Siru Ouyang, Shuohang Wang, Yang Liu, Ming Zhong, Yizhu Jiao, Dan Iter, Reid Pryzant, Chenguang Zhu, Heng Ji, Jiawei Han
  EMNLP 2023    [ Paper | Code ]
• Reaction Miner: An Integrated System for Chemical Reaction Extraction from Textual Data
  Ming Zhong, Siru Ouyang, Yizhu Jiao, Priyanka Kargupta, Leo Luo, Yanzhen Shen, Bobby Zhou, Xianrui Zhong, Xuan Liu, Hongxiang Li, Jinfeng Xiao, Minhao Jiang, Vivian Hu, Xuan Wang, Heng Ji, Martin Burke, Huimin Zhao, Jiawei Han
  EMNLP 2023 Demo    [ Paper | Code ]
• ReactIE: Enhancing Chemical Reaction Extraction with Weak Supervision
  Ming Zhong, Siru Ouyang, Minhao Jiang, Vivian Hu, Yizhu Jiao, Xuan Wang, Jiawei Han
  ACL 2023 Findings, Short Paper    [ Paper ]
• Revisiting Cross-Lingual Summarization: a Corpus-based Study and a New Benchmark with Improved Annotation
  Yulong Chen, Huajian Zhang, Yijie Zhou, Xuefeng Bai, Yueguan Wang, Ming Zhong, Jianhao Yan, Yafu Li, Judy Li, Xianchao Zhu and Yue Zhang
  ACL 2023    [ Paper | Data ]
• Unsupervised Event Chain Mining from Multiple Documents
  Yizhu Jiao, Ming Zhong, Jiaming Shen, Yunyi Zhang, Chao Zhang, Jiawei Han
  WWW 2023    [ Paper ]
• PREME: Preference-based Meeting Exploration through an Interactive Questionnaire
  Negar Arabzadeh, Ali Ahmadvand, Julia Kiseleva, Yang Liu, Ahmed Hassan Awadallah, Ming Zhong, Milad Shokouhi
  EACL 2023 Findings    [ Paper | Code ]

2022

• Towards a Unified Multi-Dimensional Evaluator for Text Generation
  Ming Zhong, Yang Liu, Da Yin, Yuning Mao, Yizhu Jiao, Pengfei Liu, Chenguang Zhu, Heng Ji and Jiawei Han
  EMNLP 2022 (Oral)    [ Paper | Code ]
• CiteSum: Citation Text-guided Scientific Extreme Summarization and Low-resource Domain Adaptation
  Yuning Mao, Ming Zhong, Jiawei Han
  EMNLP 2022    [ Paper | Code and Data ]
• UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models
  Tianbao Xie*, Chen Henry Wu*, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I. Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A. Smith, Luke Zettlemoyer, Tao Yu
  EMNLP 2022 (Oral)    [ Paper | Code | Project Page ]
• Unsupervised Multi-Granularity Summarization
  Ming Zhong, Yang Liu, Suyu Ge, Yuning Mao, Yizhu Jiao, Xingxing Zhang, Yichong Xu, Chenguang Zhu, Michael Zeng, Jiawei Han
  EMNLP 2022 Findings    [ Paper | Data ]
• Open-Vocabulary Argument Role Prediction for Event Extraction
  Yizhu Jiao, Sha Li, Yiqing Xie, Ming Zhong, Heng Ji and Jiawei Han
  EMNLP 2022 Findings    [ Paper | Code ]
• DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization
  Ming Zhong, Yang Liu, Yichong Xu, Chenguang Zhu, Michael Zeng
  AAAI 2022 (Oral)    [ Paper | Code | Dataset ]
• COLO: A Contrastive Learning Based Re-ranking Framework for One-Stage Summarization
  Chenxin An, Ming Zhong, Zhiyong Wu, Qin Zhu, Xuanjing Huang, Xipeng Qiu
  COLING 2022    [ Paper | Code ]
• Improving Abstractive Dialogue Summarization with Speaker-Aware Supervised Contrastive Learning
  Zhichao Geng, Ming Zhong, Zhangyue Yin, Xipeng Qiu and Xuanjing Huang
  COLING 2022, Short Paper (Oral)    [ Paper ]
• The Cross-lingual Conversation Summarization Challenge
  Yulong Chen*, Ming Zhong*, Xuefeng Bai*, Naihao Deng, Jing Li, Xianchao Zhu, Yue Zhang
  INLG 2022    [ Paper ]

2021

• QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization
  Ming Zhong*, Da Yin*, Tao Yu, Ahmad Zaidi, Mutethia Mutuma, Rahul Jha, Ahmed Hassan Awadallah, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, Dragomir Radev
  NAACL 2021 (Oral)    [ Paper | Dataset ]
• Enhancing Scientific Papers Summarization with Citation Graph
  Chenxin An, Ming Zhong, Yiran Chen, Danqing Wang, Xipeng Qiu, Xuanjing Huang
  AAAI 2021    [ Paper | Code | Dataset ]
• RetrievalSum: A Retrieval Enhanced Framework for Abstractive Summarization
  Chenxin An, Ming Zhong, Zhichao Geng, Jianqiang Yang, Xipeng Qiu
  arXiv 2021    [ Paper ]

2020

• Extractive Summarization as Text Matching
  Ming Zhong*, Pengfei Liu*, Yiran Chen, Danqing Wang, Xipeng Qiu, Xuanjing Huang
  ACL 2020    [ Paper | Code ]
• CDEvalSumm: An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems
  Yiran Chen*, Pengfei Liu*, Ming Zhong, Zi-Yi Dou, Danqing Wang, Xipeng Qiu, Xuanjing Huang
  EMNLP 2020 Findings    [ Paper | Code ]

2019

• Searching for Effective Neural Extractive Summarization: What Works and What's Next
  Ming Zhong*, Pengfei Liu*, Danqing Wang, Xipeng Qiu, Xuanjing Huang
  ACL 2019 (Oral)    [ Paper | Code ]
• A Closer Look at Data Bias in Neural Extractive Summarization Models
  Ming Zhong*, Danqing Wang*, Pengfei Liu*, Xipeng Qiu, Xuanjing Huang
  EMNLP 2019 Workshop on New Frontiers in Summarization    [ Paper ]
• Exploring Domain Shift in Extractive Text Summarization
  Danqing Wang*, Pengfei Liu*, Ming Zhong, Jie Fu, Xipeng Qiu, Xuanjing Huang
  arXiv 2019    [ Paper ]