基本情况

• 男，共产党员，来自于有鹤乡之称的黑龙江省齐齐哈尔市

人生格言

• 天道酬勤，持之以恒

研究兴趣

• 主要研究方向
  • 人工智能
  • 自然语言处理
  • 文本推理
  • 事理图谱
• 相关学位论文
  • 基于社会媒体的市场行情预测方法研究，博士生毕业论文，2016.6
  • 句子级中文事件抽取关键技术研究，硕士生毕业论文，2011.7

部分已发表论文

• Linyao Yang，Hongyang Chen，Zhao Li，Xiao Ding，Xindong Wu. Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling. In Proc. TKDE 2024. [PDF]
• Xiao Ding, Bibo Cai, Xue Li, Ting Liu, Bing Qin x-ECON: Explainable Event-Consumption Commonsense Reasoning In Proc. TBD 2024. [PDF]
• Zhouhao Sun, Xiao Ding, Li Du, Bibo Cai, Jinglong Gao, Ting Liu and Bing Qin Towards Generalizable and Faithful Logic Reasoning over Natural Language via Resolution Refutation. In Proc. Coling 2024. [PDF]
• Zhouhao Sun*, Li Du*, Xiao Ding, Yixuan Ma, Yang Zhao, Kaitao Qiu, Ting Liu, Bing Qin. Causal-Guided Active Learning for Debiasing Large Language Models In Proc. ACL 2024. [PDF]
• Jinglong Gao, Xiao Ding, Yiming Cui, Jianbai Zhao, Hepeng Wang, Ting Liu, Bing Qin. Self-Evolving GPT: A Lifelong Autonomous Experiential Learner. In Proc. ACL 2024.
• Jinglong Gao, Xiao Ding, Zhongyang Li, Ting Liu, Bing Qin Event Causality Identification via Competitive-Cooperative Cognition Networks. In Proc. KBS 2024. (Long Paper, Findings). [PDF]
• Yang Zhao*, Li Du*, Xiao Ding, Kai Xiong, Zhouhao Sun, Shi jun, Ting Liu, Bing Qin. Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning. In Proc. ACL 2024. (Long Paper, Findings). [PDF]
• Yirong Zeng, Xiao Ding, Yi Zhao, Xiangyu Li，Jie Zhang, Chao Yao, Ting Liu, Bing Qin. RU22Fact: Optimizing Evidence for Multilingual Explainable Fact-Checking on Russia-Ukraine Conflict. In Proc. Coling 2024. (Long Paper, Findings). [PDF]
• Tingting Wu, Xiao Ding, Li Du, Bing Qin, Ting Liu. Reasoning subevent relation over heterogeneous event graph. In Proc. KIS 2024. [PDF]
• Tingting Wu, Xiao Ding, Hao Zhang, Minji Tang, Bing Qin, Ting Liu. Uncertainty-guided label correction with wavelet-transformed discriminative representation enhancement. In Proc. NN 2024. [PDF]
• Kai Xiong, Xiao Ding, Yixin Cao, Ting Liu, Bing Qin. Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate. In Proc. EMNLP 2023. (Long Paper, Findings). [PDF]
• Jinglong Gao, Xiao Ding, Bing Qin, Ting Liu. Is ChatGPT a Good Causal Reasoner? A Comprehensive Evaluation. In Proc. EMNLP 2023. (Long Paper, Findings). [PDF]
• Tingting Wu, Xiao Ding, Hao Zhang,Jinglong Gao,Minji Tang,Li Du,Bing Qin,Ting Liu. DiscrimLoss: A Universal Loss for Hard Samples and Incorrect Samples Discrimination. IEEE Transactions on Multimedia. (SCI Index, IF=8.182)[PDF]
• Li Du, Xiao Ding, Zhouhao Su,Ting Liu,Bing Qin, Jingshuo Liu. Towards Stable Natural Language Understanding via Information Entropy Guided Debiasing. In Proc. ACL 2023. (Main Conference)[PDF]
• Tingting Wu, Xiao Ding, Minji Tang, Hao Zhang, Bing Qin,Ting Liu. NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing. In Proc. ACL 2023. (Findings)[PDF]
• Bibo Cai, Xiao Ding, Zhouhao Sun, Bing Qin, Ting Liu, Baojun Wang, Lifeng Shang. Self-supervised Logic Induction for Explainable Fuzzy Temporal Commonsense Reasoning. In Proc. AAAI 2023. (Main Conference)[PDF]
• Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin. Enhancing pretrained language models with structured commonsense knowledge for textual inference. In Proc. Journal of Knowledge-Based Systems. (SCI Index, IF=8.139). [PDF]
• Kai Xiong, Xiao Ding, Zhongyang Li, Li Du, Ting Liu, Bing Qin, Yi Zheng, Baoxing Huai. ReCo: Reliable Causal Chain Reasoning via Structural Causal Recurrent Neural Networks. In Proc. EMNLP 2022. (Long Paper, Main Conference). [PDF]
• Tingting Wu, Xiao Ding, Minji Tang, Hao Zhang, Bing Qin, Ting Liu. STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processin. In Proc. EMNLP 2022. (Long Paper, Main Conference). [PDF]
• Xiao Ding, Bowen Chen, Li Du, Bing Qin, Ting Liu. CogBERT: Cognition-Guided Pre-trained Language Models. In Proc. COLING 2022. (Long Paper). [PDF]
• Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin. e-CARE: a New Dataset for Exploring Explainable Causal Reasoning. In Proc. ACL 2022. (Long Paper, Main Conference). [PDF]
• Li Du, Xiao Ding, Yue Zhang, Ting Liu, Bing Qin. A Graph Enhanced BERT Model for Event Prediction. In Proc. ACL 2022. (Long Paper, Findings). [PDF]
• Bibo Cai, Xiao Ding, Bowen Chen, Li Du, Ting Liu. Mitigating Reporting Bias for Semi-supervised Temporal Commonsense Inference with Probabilistic Soft Logic. In Proc. AAAI 2022. (Long Paper, Main Conference).
• Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin. ExCAR: Event Graph Knowledge Enhanced Explainable Causal Reasoning. In Proc. ACL 2021. (Long Paper, Main Conference). [PDF]
• Li Du, Xiao Ding, Ting Liu, Bing Qin. Learning Event Graph Knowledge for Abductive Reasoning. In Proc. ACL 2021. (Long Paper, Main Conference). [PDF]
• Jihao Shi, Xiao Ding, Ting Liu, Bing Qin. Neural Natural Logic Inference for Interpretable Question Answering. In Proc. EMNLP 2021. (Long Paper, Main Conference). [PDF]
• Xiao Ding, Jihao Shi, Junwen Duan, Bing Qin, Ting Liu. Quantifying the effects of long-term news on stock markets on the basis of the multikernel Hawkes process. In Proc. Science China Information Sciences 64 (9), 1-13. (SCI Index, IF=4.38). [PDF]
• Zhongyang Li, Xiao Ding, Ting Liu. TransBERT: A Three-Stage Pre-training Technology for Story-Ending Prediction. In Proc. ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), 2021, 20(1): 1-20. (SCI Index, IF=1.42). [PDF]
• Xiao Ding, Dingkui Hao, Yuewei Zhang, Kuo Liao, Zhongyang Li, Bing Qin, Ting Liu. HIT-SCIR at SemEval-2020 Task 5: Training Pre-trained Language Model with Pseudo-labeling Data for Counterfactuals Detection. In Proc. SemEval 2020. We won the first place (1st) in Subtask 1 of Task 5.
• Zhongyang Li, Xiao Ding, Ting Liu, Edward Hu, Benjamin Van Durme. Guided Generation of Cause and Effect. In Proc. IJCAI 2020 (Long Paper, accept rate = 12.6%). [PDF]
• Junwen Duan, Xiao Ding, Yue Zhang, Ting Liu. TEND: A Target-dependent Representation Learning Framework for News Document. In IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 2019. [PDF]
• Zhongyang Li, Xiao Ding, Ting Liu. Story Ending Prediction by Transferable BERT. In Proc. IJCAI 2019 (Long Paper, accept rate = 17.8%). [PDF]
• Xiao Ding, Kuo Liao, Ting Liu, Zhongyang Li, Junwen Duan. Event Representation Learning Enhanced with External Commonsense Knowledge. In Proc. EMNLP 2019 (Long Paper, accept rate = 23.8%). [PDF][DATA&CODE]
• Li Du, Xiao Ding, Ting Liu, Zhongyang Li. Modeling Event Background for If-Then Commonsense Reasoning Using Contextaware Variational Autoencoder. In Proc. EMNLP 2019 (Long Paper, accept rate = 23.8%). [PDF]
• Xiao Ding, Bibo Cai, Ting Liu, Qiankun Shi. Domain Adaptation via Tree Kernel Based Maximum Mean Discrepancy for User Consumption Intention Identification. In Proc. IJCAI 2018 (Long Paper, accept rate = 20%). [PDF] [DATA&CODE]
• Zhongyang Li, Xiao Ding, Ting Liu. Constructing Narrative Event Evolutionary Graph for Script Event Prediction. In Proc. IJCAI 2018 (Long Paper, accept rate = 20%). [PDF] [DATA&CODE]
• Zhongyang Li, Xiao Ding, Ting Liu. Generating Reasonable and Diversified Story Ending Using Sequence to Sequence Model with Adversarial Training. In Proc. COLING 2018 (Long Paper, accept rate = 37.4%). [PDF]
• Junwen Duan, Yue Zhang, Xiao Ding, Ching-Yun Chang, Ting Liu. Learning Target Dependent Representations of Financial News Documents. In Proc. COLING 2018 (Long Paper, accept rate = 37.4%). [PDF]
• Junwen Duan, Xiao Ding, Ting Liu. Learning Sentence Representations over Tree Structures for Target-dependent Classification. In Proc. NAACL 2018 (Long Paper, accept rate = 32%). [PDF]
• Xiao Ding, Yue Zhang, Ting Liu, Junwen Duan. Knowledge-Driven Event Embedding for Stock Prediction. In Proc. COLING 2016 (Long Paper, accept rate = 32%). [PDF]
• Ting Liu, Xiao Ding, Yiheng Chen, Hanchen Chen, Maosheng Guo. Predicting Movie Box-Office Revenues by Exploiting Large-Scale Social Media Content. Multimedia Tools and Applications. (SCI Index, Impact Factor: 1.346, Corresponding Author). 2016. [PDF] [Demo]
• Xiao Ding, Bing Qin, Ting Liu. BUEES: a Bottom-Up Event Extraction System. Frontiers of Information Technology & Electronic Engineering. (SCI Index, Impact Factor: 0.415). 2015. [PDF]
• Xiao Ding, Yue Zhang, Ting Liu, Junwen Duan. Deep Learning for Event-Driven Stock Prediction. In Proc. IJCAI 2015 (Long Paper, accept rate = 28%). [PDF] [Slides] [Poster]
• Xiao Ding, Ting Liu, Junwen Duan, Jianyun Nie. Mining User Consumption Intention from Social Media via Domain Adaptive Convolutional Neural Network. In Proc. AAAI 2015 (long paper, accept rate = 26.67%). [PDF]
• Xiao Ding, Yue Zhang, Ting Liu, Junwen Duan. Using Structured Events to Predict Stock Price Movement: An Empirical Investigation. In Proc. EMNLP 2014 (Long Paper, accept rate = 28%). [PDF] [DATA]
• Xiao Ding, Zhicheng Dou, Bing Qin, Ting Liu, Ji-Rong Wen. Improving Web Search Ranking by Incorporating Structured Annotation of Queries. In Proc. EMNLP 2013 (Long Paper, accept rate = 27%). [PDF]
• Xiao Ding, Bing Qin, Ting Liu. Building Chinese Event Type Paradigm Based on Trigger Clustering. In Proc. IJCNLP 2013 (Long Paper, accept rate = 23.4%). [PDF] [Demo]

学术报告

• 社会媒体处理前沿综述. [Slides] 2019年第十八届中国计算语言学大会前沿技术综述
• 事理图谱构建及应用. [Slides] 2019年第八届全国社会媒体处理大会青年精英科学家报告
• 基于增强学习的股市涨跌预测技术. [Slides] 2018年第七届全国社会媒体处理大会智能金融论坛
• 基于社会媒体的消费意图挖掘. [Slides] 2016年中文信息学会社会媒体处理专委会“计算社会学”前沿论坛特邀报告

学术服务

• 中文信息学会社会媒体处理专委会秘书、常务委员；中文信息学会语言与知识计算专委会委员；中文信息学会青年工作委员会委员；
• 期刊审稿人：CL, TKDE, TOIS, TNNLS, TIST，IPM, KBS，Big Data Research，中国科学
• 会议审稿人：ACL, AAAI, IJCAI, WWW, EMNLP等

兴趣爱好

• 羽毛球、游泳、排球、足球

联系方式

• E-mail：xding at ir dot hit dot edu dot cn
• 通信地址：哈尔滨工业大学科创大厦，150001