Iโm Kai Xiong, a Ph.D. student in Research Center for Social Computing and Interactive Robotics (SCIR), at Harbin Institute of Technology (HIT, China). I am co-advised by Prof. Ting Liu and Prof. Xiao Ding. My research interests lie in event reasoning, eventic graph, and large language models.
๐ Publications
2026
- Diagnosing and Remedying Knowledge Deficiencies in LLMs via Label-free Curricular Meaningful Learning. Kai Xiong, Xiao Ding, Li Du, Jiahao Ying, Ting Liu, Bing Qin, Yixin Cao. ICLR 2026.
- Consolidation or Adaptation? PRISM: Disentangling SFT and RL Data via Gradient Concentration. Yang Zhao, Yangou Ouyang, Xiao Ding, Hepeng Wang, Bibo Cai, Kai Xiong, Jinglong Gao, Zhouhao Sun, Li Du, Bing Qin, Ting Liu. ACL 2026.
- Maestro: Meta-learning adaptive estimation of scalarization trade-offs for reward optimization. Yang Zhao, Hepeng Wang, Xiao Ding, Yangou Ouyang, Bibo Cai, Kai Xiong, Jinglong Gao, Zhouhao Sun, Li Du, Bing Qin, Ting Liu. ACL 2026.
- Is EEG-to-Text Feasible in Real-World Scenarios? An In-Depth Analysis Using a Neuropsychology-Inspired Benchmark. Zihan Zhang, Yu Bao, Xiao Ding, Tianyi Jiang, Kai Xiong. ACL 2026.
- MDC-Bench: A Multidisciplinary Causal Benchmark Based on Causal Structures for Evaluating Large Language Models. Peng Wang, Yuxiong Yan, Xiao Ding, Kai Xiong, Bibo Cai, Chao Peng, Yutai Hou, Dandan Tu, Bing Qin, Ting Liu. Findings of ACL 2026.
- Optimizing Automated Jailbreak Attacks on Large Language Models via Experience Accumulation. Yuxin Zhou, Xiao Ding, Yijia Meng, Tianle Chang, Jinglong Gao, Zihan Zhang, Kai Xiong, Qi Shi. ICASSP 2026.
- Proactive Safety Deliberation: Guiding Large Reasoning Models with Distilled Principles. Yuxin Zhou, Xiao Ding, Qi Shi, Ye He, Kai Xiong, Yijia Meng, Tianle Chang, Jinglong Gao. ICASSP 2026.
- Do LLMs Signal When Theyโre Right? Evidence from Neuron Agreement. Kang Chen, Yaoning Wang, Kai Xiong, Zhuoka Feng, Yu Minshen, Wenhe Sun, Haotian Chen, Yixin Cao. ICML 2026 (Spotlight).
2025
- Think Straight or Think Again? Continual Joint Learning of Deduction, Abduction, and Induction. Kai Xiong, Xiao Ding, Yixin Cao, Yang Zhao, Bing Qin, Ting Liu. Neural Networks (IF=6.3).
- Com$^2$: A Causal-Guided Benchmark for Exploring Complex Commonsense Reasoning in Large Language Models. Kai Xiong, Xiao Ding, Yixin Cao, Yuxiong Yan, Li Du, Yufei Zhang, Jinglong Gao, Jiaqian Liu, Bing Qin, Ting Liu. ACL 2025.
- Supervised Fine-Tuning Achieve Rapid Task Adaption Via Alternating Attention Head Activation Patterns. Yang Zhao, Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin. ACL 2025.
- Beyond Similarity: A Gradient-based Graph Method for Instruction Tuning Data Selection. Yang Zhao, Li Du, Xiao Ding, YangouOuyang, Hepeng Wang, Kai Xiong, Jinglong Gao, Zhouhao Sun, Dongliang Xu, Qing Yang, Dongchen Li, Bing Qin, Ting Liu. ACL 2025.
- Natural Logic at the Core: Dynamic Rewards for Entailment Tree Generation. Jihao Shi, Xiao Ding, Kai Xiong, Hengwei Zhao, Bing Qin, Ting Liu. ACL 2025 Findings.
- UFO-RL: Uncertainty-Focused Optimization for Efficient Reinforcement Learning Data Selection. Yang Zhao, Kai Xiong, Xiao Ding, Li Du, Yangou Ouyang, Zhouhao Sun, Jiannan Guan, Wenbin Zhang, Bin Liu, Dong Hu, Bing Qin, Ting Liu. NeurIPS 2025.
- Necessary and sufficient knowledge enhanced collaborative logical reasoning in LLMs. Peng Wang, Xiao Ding, Kai Xiong, Bing Qin, Ting Liu. Neural Networks (IF=6.3).
2024
- Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance. Kai Xiong, Xiao Ding, Ting Liu, Bing Qin, Dongliang Xu, Qing Yang, Hongtao Liu, Yixin Cao. NeurIPS 2024.
- Intuitive or Dependent? Investigating LLMsโ Behavior Style to Conflicting Prompts. Jiahao Ying, Yixin Cao, Kai Xiong, Yidong He, Long Cui, Yongbin Liu. ACL 2024.
- Deciphering the lmpact of Pretraining Data on Large Language Models through Machine Unlearning. Yang Zhao, Li Du, Xiao Ding, Kai Xiong, Zhouhao Sun, Jun Shi, Ting Liu, Bing Qin. ACL 2024 Findings.
2023
- Examining Inter-consistency of Large Language Models Collaboration: An in-depth Analysis via Debate. Kai Xiong, Xiao Ding, Yixin Cao, Ting Liu, Bing Qin. EMNLP 2023 Findings.
- Improving Cross-task Generalization with Step-by-step Instructions. Yang Wu, Yanyan Zhao, Zhongyang Li, Bing Qin, Kai Xiong. Science China-Information Sciences (IF=7.6).
2022
- ReCo: Reliable Causal Chain Reasoning via Structural Causal Recurrent Neural Networks. Kai Xiong, Xiao Ding, Zhongyang Li, Li Du, Ting Liu, Bing Qin, Yi Zheng, Baoxing Huai. EMNLP 2022.
- e-CARE: A New Dataset for Exploring Explainable Causal Reasoning. Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin. ACL 2022.
- A Graph Enhanced Bert Model for Event Prediction. Li Du, Xiao Ding, Yue Zhang, Kai Xiong, Ting Liu, Bing Qin. ACL 2022 Findings.
- Enhancing Pretrained Language Models with Structured Commonsense Knowledge for Textual Inference. Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin. Knowledge-Based Systems (IF=7.6).
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2021
- ExCAR: Event Graph Knowledge Enhanced Explainable Causal Reasoning. Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin. ACL 2021.
- Heterogeneous Graph Knowledge Enhanced Stock Market Prediction. Kai Xiong, Xiao Ding, Li Du, Ting Liu, Bing Qin. AI Open (IF=14.8).
๐ Honors and Awards
- 2024 National Scholarship for Doctoral Students
- 2024 Outstanding Student Award of Harbin Institute of Technology
- 2024 Top Reviewer of NeurIPS 2024 (8.6%, 1,304 of 15,160 reviewers)
- 2021 CCKS 2021 Best Chinese Paper Runner-up Award
- 2021 First Prize in the Future Cup AI Academic Contest
๐ Educations
- 2015.09 - 2019.06, Wuhan University, China. Bachelor of Science, Geographic Information Science.
- 2019.09 - 2021.06, Harbin Institute of Technology, China. Master of Engineering, Computer Science.
- Research Center for Social Computing and Information Retrieval (SCIR)
- Advisor: Prof. Ting Liu
- 2022.07 - 2023.08, Singapore Management University, Singapore. Research Assistant, School of Computing and Information Science.
- Advisor: Prof. Yixin Cao
- 2021.09 - Now, Harbin Institute of Technology, China. Ph.D. Candidate
- Research Center for Social Computing and Information Retrieval (SCIR)
- Advisors: Prof. Ting Liu and Xiao Ding
๐ผ Internships
- 2021.10 - 2022.07, Huawei Cloud, China. AI Algorithm Engineer.
- 2023.12 - 2024.10, Duxiaoman Financial Technology, China. LLMs Algorithm Engineer.
๐ Academic Services
- Reviewers of Top AI Conferences
- ACL/ARR: 2021, 2022, 2023, 2024, 2025
- NeurIPS: 2024, 2025
- EMNLP/ARR: 2022, 2023
- KDD: 2024
- WWW: 2025
- ICML: 2025
- Reviewers of Other Conferences
- CCKS
- NLPCC
- CCL