Yuexiang XIE

Alibaba Group
Email: yuexiang.xyx AT alibaba-inc.com

Work Experiences

• July 2020 - Now, Alibaba Group, Hang Zhou.

Publications (google scholar, dblp)

[2024]

• Very Large-Scale Multi-Agent Simulation in AgentScope
  • Xuchen Pan, Dawei Gao, Yuexiang Xie, Yushuo Chen, Zhewei Wei, Yaliang Li, Bolin Ding, Ji-Rong Wen, Jingren Zhou
  • arXiv, 2024 [code]
• Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization
  • Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He
  • arXiv, 2024 [code]
• $\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
  • Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He
  • In NeurIPS, 2024 [code]
• Understanding Byzantine Robustness in Federated Learning with A Black-box Server
  • Fangyuan Zhao, Yuexiang Xie, Xuebin Ren, Bolin Ding, Shusen Yang, Yaliang Li
  • arXiv, 2024 [code]
• Exploring Selective Layer Fine-Tuning in Federated Learning
  • Yuchang Sun, Yuexiang Xie, Bolin Ding, Yaliang Li, Jun Zhang
  • arXiv, 2024
• Agent-Oriented Planning in Multi-Agent Systems
  • Ao Li, Yuexiang Xie, Songze Li, Fugee Tsung, Bolin Ding, Yaliang Li
  • arXiv, 2024
• Data-Juicer: A One-Stop Data Processing System for Large Language Models
  • Daoyuan Chen, Yilun Huang, Zhijian Ma, Hesen Chen, Xuchen Pan, Ce Ge, Dawei Gao, Yuexiang Xie, Zhaoyang Liu, Jinyang Gao, Yaliang Li, Bolin Ding, Jingren Zhou
  • In SIGMOD, 2024 [code]
• Is Sharing Neighbor Generator in Federated Graph Learning Safe?
  • Liuyi Yao, Zhen Wang, Yuexiang Xie, Yaliang Li, Weirui Kuang, Daoyuan Chen, Bolin Ding
  • In IEEE Transactions on Knowledge and Data Engineering, 2024
• FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning
  • Weirui Kuang, Bingchen Qian, Zitao Li, Daoyuan Chen, Dawei Gao, Xuchen Pan, Yuexiang Xie, Yaliang Li, Bolin Ding, Jingren Zhou
  • In KDD, 2024 [code]
• Privacy-Preserving Cross-Domain Recommendation with Federated Graph Learning
  • Changxin Tian, Yuexiang Xie, Xu Chen, Yaliang Li, Xin Zhao
  • In TOIS, 2024
• When to Trust LLMs: Aligning Confidence with Response Quality
  • Shuchang Tao, Liuyi Yao, Hanxing Ding, Yuexiang Xie, Qi Cao, Fei Sun, Jinyang Gao, Huawei Shen, Bolin Ding
  • In ACL, 2024 [code]

[2023]

• Tunable Soft Prompts are Messengers in Federated Learning
  • Chenhe Dong*, Yuexiang Xie*, Bolin Ding, Ying Shen, Yaliang Li
  • In EMNLP, 2023 [code]
• FederatedScope: A Flexible Federated Learning Platform for Heterogeneity
  • Yuexiang Xie*, Zhen Wang*, Daoyuan Chen, Dawei Gao, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou
  • In VLDB, 2023 [code]
• Counterfactual Debiasing for Generating Factually Consistent Text Summaries
  • Chenhe Dong, Yuexiang Xie, Yaliang Li, Ying Shen
  • arXiv, 2023
• Source-Free Unsupervised Domain Adaptation for Question Answering
  • Zishuo Zhao, Yuexiang Xie, Jingyou Xie, Zhenzhou Lin, Yaliang Li, Ying Shen
  • In ICASSP, 2023
• FS-Real: A Real-World Cross-Device Federated Learning Platform
  • Dawei Gao, Daoyuan Chen, Zitao Li, Yuexiang Xie, Xuchen Pan, Yaliang Li, Bolin Ding, Jingren Zhou
  • In VLDB Demo, 2023
• Towards Real-World Cross-Device Federated Learning
  • Daoyuan Chen, Dawei Gao, Yuexiang Xie, Xuchen Pan, Zitao Li, Yaliang Li, Bolin Ding, Jingren Zhou
  • In KDD, 2023

[2022]

• iFlood: A Stable and Effective Regularizer
  • Yuexiang Xie, Zhen Wang, Yaliang Li, Ce Zhang, Jingren Zhou, Bolin Ding
  • In ICLR, 2022
• Collaborating Heterogeneous Natural Language Processing Tasks via Federated Learning
  • Chenhe Dong*, Yuexiang Xie*, Bolin Ding, Ying Shen, Yaliang Li
  • arXiv, 2022
• Finding Meta Winning Ticket to Train Your MAML
  • Dawei Gao, Yuexiang Xie, Zimu Zhou, Zhen Wang, Yaliang Li, Bolin Ding
  • In KDD, 2022
• Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering
  • Changxin Tian, Yuexiang Xie, Yaliang Li, Nan Yang, Wayne Xin Zhao
  • In SIGIR, 2022
• Explainable Neural Rule Learning
  • Shaoyun Shi, Yuexiang Xie, Zhen Wang, Bolin Ding, Yaliang Li, Min Zhang
  • In WWW, 2022 [code]
• FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning
  • Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou
  • In KDD, 2022, Best Paper Award at Applied Data Science Track. [code]
• A Practical Introduction to Federated Learning
  • Yaliang Li, Bolin Ding, Zhen Wang, Yuexiang Xie, Dawei Gao, Liuyi Yao, Daoyuan Chen, Weirui Kuang, Hongzhu Shi, Jingren Zhou
  • In KDD Tutorial, 2022 [website]
• A Benchmark for Federated Hetero-Task Learning
  • Liuyi Yao, Dawei Gao, Zhen Wang, Yuexiang Xie, Weirui Kuang, Daoyuan Chen, Haohui Wang, Chenhe Dong, Bolin Ding, Yaliang Li
  • arXiv, 2022 [code]

[2021]

• Factual Consistency Evaluation for Text Summarization via Counterfactual Estimation
  • Yuexiang Xie, Fei Sun, Yang Deng, Yaliang Li, Bolin Ding
  • In EMNLP, 2021 [code]
• FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data
  • Yuexiang Xie*, Zhen Wang*, Yaliang, Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou
  • In KDD, 2021
• Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge
  • Yang Deng*, Yuexiang Xie*, Yaliang Li, Min Yang, Wai Lam, Ying Shen
  • In TOIS, 2021
• AutoML: From Methodology to Application
  • Yaliang Li, Zhen Wang, Yuexiang Xie, Bolin Ding, Kai Zeng, Ce Zhang
  • In CIKM Tutorial, 2021 [website]

[2020 & before]

• Attentive User-Engaged Adversarial Neural Network for Community Question Answering
  • Yuexiang Xie, Ying Shen, Yaliang Li, Min Yang, Kai Lei
  • In AAAI, 2020
• Joint Learning of Answer Selection and Answer Summary Generation in Community Question Answering
  • Yang Deng, Wai Lam, Yuexiang Xie, Daoyuan Chen, Yaliang Li, Min Yang, Ying Shen
  • In AAAI, 2020
• Multi-task Learning with Multi-view Attention for Answer Selection and Knowledge Base Question Answering
  • Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Nan Du, Wei Fan, Kai Lei, Ying Shen
  • In AAAI, 2019
• Generative Adversarial Fusion Network for Class Imbalance Credit Scoring
  • Kai Lei, Yuexiang Xie, Shangru Zhong, Jingchao Dai, Min Yang, Ying Shen
  • In Neural Computing and Application, 2019
• Path-based Reasoning with Constrained Type Attention for Knowledge Graph Completion
  • Kai Lei, Jin Zhang, Yuexiang Xie, Desi Wen, Daoyuan Chen, Min Yang, Ying Shen
  • In Neural Computing and Application, 2019
• Feature-Aware Attentive Convolutional Neural Network for Sequence Processing
  • Jingchao Dai, Kaiqi Yuan, Yuexiang Xie, Ying Shen
  • In KSEM, 2019

Awards & Scholarships

• Best Paper Award at Applied Data Science Track, KDD’22
• KDD Cup, AutoML Track, 4/149, May 2020.
• National Scholarship, Sep 2014.

Program Committee Memberships

• Regular Reviewer (or PC Member): ICLR, ICML, NeurIPS, NeurIPS Datasets and Benchmarks, ACL ARR, KDD, WWW, AAAI, TNNLS, TBD