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Hello! I am Xiang, a PhD student in the Computational Logic and Argumentation group (CLArg) of Department of Computing at Imperial College London, working under the supervision of Prof. Francesca Toni and Dr. Nico Potyka. My research, funded by the ERC project on Argumentation-based Deep Interactive Explanations, focuses on explainable AI (XAI) and Computational Argumentation (CA), particularly the explainability of Quantitative Bipolar Argumentation Frameworks (QBAFs).

Before starting my PhD, I worked as a machine learning research and development engineer in the Department of Search Science at Baidu for one year. During my time at Baidu, I was involved in developing advanced search recommender algorithms and systems to optimize user experience and search engine performance.

Research

• Applying Attribution Explanations in Truth-Discovery Quantitative Bipolar Argumentation Frameworks
  X. Yin, N. Potyka, F. Toni. The 2nd International Workshop on Argumentation for eXplainable AI (ArgXAI @ COMMA), 2024.

• Contribution functions for quantitative bipolar argumentation graphs: A principle-based analysis
  T. Kampik, N. Potyka, X. Yin, K. Čyras, F. Toni. International Journal of Approximate Reasoning (IJAR), 2024.

• Contestable AI Needs Computational Argumentation
  F. Leofante, H. Ayoobi, A. Dejl, G. Freedman, D. Gorur, J. Jiang, G. Paulino-Passos, A. Rago, A. Rapberger, F. Russo, X. Yin, D. Zhang, F. Toni. The 21st International Conference on Principles of Knowledge Representation and Reasoning (KR), 2024.

• CE-QArg: Counterfactual Explanations for Quantitative Bipolar Argumentation Frameworks
  X. Yin, N. Potyka, F. Toni. The 21st International Conference on Principles of Knowledge Representation and Reasoning (KR), 2024.

• Explaining Arguments’ Strength: Unveiling the Role of Attacks and Supports
  X. Yin, N. Potyka, F. Toni. The 33rd International Joint Conference on Artificial Intelligence (IJCAI), 2024.

• Argument Attribution Explanations in Quantitative Bipolar Argumentation Frameworks
  X. Yin, N. Potyka, F. Toni. The 26th European Conference on Artificial Intelligence (ECAI), 2023.

• Explaining Random Forests Using Bipolar Argumentation and Markov Networks
  N. Potyka, X. Yin, F. Toni. The 37th AAAI Conference on Artificial Intelligence (AAAI), 2023.

• On the Tradeoff Between Correctness and Completeness in Argumentative Explainable AI
  N. Potyka, X. Yin, F. Toni. The 1st International Workshop on Argumentation for eXplainable AI (ArgXAI @ COMMA), 2022.