Yuexiang XIE

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

Work Experiences

• July 2020 - Now, Alibaba Group, Hangzhou.

Publications (google scholar, dblp)

[2025]

• On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weighting
  • Wenhao Zhang, Yuexiang Xie, Yuchang Sun, Yanxi Chen, Guoyin Wang, Yaliang Li, Bolin Ding, Jingren Zhou
  • arXiv, 2025 [code]
• AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
  • Dawei Gao, Zitao Li, Yuexiang Xie, Weirui Kuang, Liuyi Yao, Bingchen Qian, Zhijian Ma, Yue Cui, Haohao Luo, Shen Li, Lu Yi, Yi Yu, Shiqi He, Zhiling Luo, Wenmeng Zhou, Zhicheng Zhang, Xuguang He, Ziqian Chen, Weikai Liao, Farruh Isakulovich Kushnazarov, Yaliang Li, Bolin Ding, Jingren Zhou
  • arXiv, 2025 [code]
• Trinity-rft: A general-purpose and unified framework for reinforcement fine-tuning of large language models
  • Xuchen Pan, Yanxi Chen, Yushuo Chen, Yuchang Sun, Daoyuan Chen, Wenhao Zhang, Yuexiang Xie, Yilun Huang, Yilei Zhang, Dawei Gao, Weijie Shi, Yaliang Li, Bolin Ding, Jingren Zhou
  • arXiv, 2025 [[code][https://github.com/modelscope/Trinity-RFT]]
• Agent-Oriented Planning in Multi-Agent Systems
  • Ao Li, Yuexiang Xie, Songze Li, Fugee Tsung, Bolin Ding, Yaliang Li
  • In ICLR, 2025 [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
  • In ICLR, 2025 [code]
• Knowledge Graph-Guided Retrieval Augmented Generation
  • Xiangrong Zhu, Yuexiang Xie, Yi Liu, Yaliang Li, Wei Hu
  • In NAACL, 2025 [code]
• KIMAs: A Configurable Knowledge Integrated Multi-Agent System
  • Zitao Li*, Fei Wei*, Yuexiang Xie*, Dawei Gao, Weirui Kuang, Zhijian Ma, Bingchen Qian, Yaliang Li, Bolin Ding
  • arXiv, 2025
• Language Adaptation of Large Language Models: An Empirical Study on LLaMA2
  • Shumin Wang, Yuexiang Xie, Bolin Ding, Jinyang Gao, Yanyong Zhang
  • In COLING, 2025
• Enhancing Factual Consistency in Text Summarization via Counterfactual Debiasing
  • Zhenqing Ling, Yuexiang Xie, Chenhe Dong, Ying Shen
  • In COLING, 2025 [code]
• Tree-based Models for Vertical Federated Learning: A Survey
  • Bingchen Qian, Yuexiang Xie, Yaliang Li, Bolin Ding, Jingren Zhou
  • In ACM Computing Surveys, 2025
• Comprehensive Evaluation and Analysis for NSFW Concept Erasure in Text-to-Image Diffusion Models
  • Die Chen, Zhiwen Li, Cen Chen, Yuexiang Xie, Xiaodan Li, Jinyan Ye, Yingda Chen, Yaliang Li
  • In NeurIPS Datasets & Benchmarks Track, 2025

[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]
• $\beta$-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
• 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 TKDE, 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