Revery: From Proof-of-Concept to Exploitable. - Yan Wang; Chao Zhang 008; Xiaobo Xiang; Zixuan Zhao; Wenjie Li 006; Xiaorui Gong; Bingchang Liu; Kaixiang Chen; Wei Zou (CCS, 2018)

αDiff: cross-version binary code similarity detection with DNN. - Bingchang Liu; Wei Huo; Chao Zhang 008; Wenchao Li; Feng Li 045; Aihua Piao; Wei Zou (ASE, 2018)

1dVul: Discovering 1-Day Vulnerabilities through Binary Patches. - Jiaqi Peng; Feng Li 045; Bingchang Liu; Lili Xu; Binghong Liu; Kai Chen; Wei Huo (DSN, 2019)

A large-scale empirical study on vulnerability distribution within projects and the lessons learned. - Bingchang Liu; Guozhu Meng; Wei Zou; Qi Gong; Feng Li 045; Min Lin; Dandan Sun; Wei Huo; Chao Zhang 008 (ICSE, 2020)

DCDFNE: build dataset to evaluate binary codes diffing tools and train deep learning models. - Ke Zhan; Zhonghua Lu; Bingchang Liu (ISPA/BDCloud/SocialCom/SustainCom, 2020)

Exploiting the Trust Between Boundaries: Discovering Memory Corruptions in Printers via Driver-Assisted Testing. - Xiaoyu He; Erick Bauman; Feng Li 045; Lei Yu; Linyu Li 004; Bingchang Liu; Aihua Piao; Kevin W. Hamlen; Wei Huo; Wei Zou (LCTES, 2020)

An Empirical Study on Change-induced Incidents of Online Service Systems. - Yifan Wu 002; Bingxu Chai; Ying Li 012; Bingchang Liu; Jianguo Li; Yong Yang; Wei Jiang 011 (ICSE-SEIP, 2023)

MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning. - Bingchang Liu; Chaoyu Chen; Cong Liao; Zi Gong; Huan Wang; Zhichao Lei; Ming Liang; Dajun Chen; Min Shen; Hailian Zhou; Hang Yu 002; Jianguo Li (CoRR, 2023)

A Survey on Language Models for Code. - Ziyin Zhang; Chaoyu Chen; Bingchang Liu; Cong Liao; Zi Gong; Hang Yu 002; Jianguo Li; Rui Wang 015 (CoRR, 2023)

CoBa: Convergence Balancer for Multitask Finetuning of Large Language Models. - Zi Gong; Hang Yu 002; Cong Liao; Bingchang Liu; Chaoyu Chen; Jianguo Li (EMNLP, 2024)

MicroFuzz: An Efficient Fuzzing Framework for Microservices. - Peng Di; Bingchang Liu; Yiyi Gao (ICSE-SEIP, 2024)

CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model. - Peng Di; Jianguo Li; Hang Yu 002; Wei Jiang 011; Wenting Cai; Yang Cao; Chaoyu Chen; Dajun Chen; Hongwei Chen; Liang Chen; Gang Fan; Jie Gong; et al. (ICSE-SEIP, 2024)

MFTCoder: Boosting Code LLMs with Multitask Fine-Tuning. - Bingchang Liu; Chaoyu Chen; Zi Gong; Cong Liao; Huan Wang; Zhichao Lei; Ming Liang; Dajun Chen; Min Shen; Hailian Zhou; Wei Jiang 011; Hang Yu 002; et al. (KDD, 2024)

Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code. - Ziyin Zhang; Chaoyu Chen; Bingchang Liu; Cong Liao; Zi Gong; Hang Yu 002; Jianguo Li; Rui Wang 015 (Trans. Mach. Learn. Res., 2024)

Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM. - Codefuse; Wenting Cai; Yuchen Cao; Chaoyu Chen; Chen Chen; Siba Chen; Qing Cui; Peng Di; Junpeng Fang; Zi Gong; Ting Guo; Zhengyu He; et al. (CoRR, 2025)

Code Graph Model (CGM): A Graph-Integrated Large Language Model for Repository-Level Software Engineering Tasks. - Hongyuan Tao; Ying Zhang; Zhenhao Tang; Hongen Peng; Xukun Zhu; Bingchang Liu; Yingguang Yang; Ziyin Zhang; Zhaogui Xu; Haipeng Zhang; Linchao Zhu; Rui Wang 015; et al. (CoRR, 2025)