Fengran Mo

Ph.D. Student

RALI Lab, Department of Computer Science and Operations Research (DIRO), Université de Montréal, Montréal, Québec, Canada

Email: fengran.mo@umontreal.ca

I am a third-year Ph.D. student at the RALI Lab of Université de Montréal. I am fortunate to be advised by Prof. Jian-Yun Nie. I obtained my Master degree in Computer Science from Université de Montréal, Canada (08.2022), advised by Prof. Jian-Yun Nie, and Bachelor degree from Dalian University of Technology, China (07.2020), advised by Prof. Degen Huang. Specifically, my research interests focus on information retrieval and natural language processing, especially conversational search, multilingual NLP, retrieval-augmented generation (RAG), etc. I have ever received Best Paper Award Nominations in WWW 2023 and was awarded the Canada Mitacs Globalink Research Scholarship (2020), Montreal AI Scholarship (2021), and Bourses d'excellence Merit Student (2021-2023). I also served as a reviewer for top conferences and journals, including ACL, EMNLP, NAACL, COLING, WSDM, CIKM, WWW, ECIR, TOIS, etc.

News

  • 2024.11: Our paper "A User-Centric Multi-Intent Benchmark for Evaluating Large Language Models" obtains Resource Award (only two) in EMNLP 2024.
  • 2024.10: We write a new survey about Conversational Search. See more details.
  • 2024.9: Four papers have been accepted by EMNLP 2024 (three main, one findings).
  • 2024.7: Two papers have been accepted by CIKM 2024.
  • 2024.6: I started as an applied scientist intern in the Amazon Rufus team at Palo Alto.
  • 2024.5: We write a new survey about Large Language Models with Multilingualism. See more details.

    • Industrial Experience

  • Amazon, Applied Scientist Intern, Conversational AI, LLMs-Rufus. Palo Alto, CA, US, Jul. 2024 - Dec. 2024.
  • Ant Group, Research Intern, Text Differential Privacy, NLP, Machine learning. Hangzhou, CHN, May. 2021 - Nov. 2021.
  • DiDi, Algorithm Intern, Semantic matching, NLP, Deep learning. Beijing, CHN, May. 2020 - Oct. 2020.

    • Visiting Experience

  • Tsinghua University, THUNLP Lab, NLP, Conversational AI. Beijing, CHN, Mar. 2022 - Aug. 2022, hosted by Prof. Yang Liu.
  • Dalhousie University, MALNIS Lab, Medical NLP. Halifax, NS, CA, Jun. 2019 - Sep. 2019, hosted by Prof. Evangelos Milios.

    • Publications [Google Scholar]

     (* denotes equal contributions)
  • Fengran Mo, Kelong Mao, Ziliang Zhao, Hongjin Qian, Haonan Chen, Yiruo Cheng, Xiaoxi Li, Yutao Zhu, Zhicheng Dou, Jian-Yun Nie. A Survey of Conversational Search. In ArXiv 2024.
  • Fengran Mo, Abbas Ghaddar, Kelong Mao, Mehdi Rezagholizadeh, Boxing Chen, Qun Liu, Jian-Yun Nie. CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Search. In Proceedings of EMNLP 2024.
  • Fengran Mo, Chen Qu, Kelong Mao, Yihong Wu, Zhan Su, Kaiyu Huang, Jian-Yun Nie. Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Search. In Proceedings of CIKM 2024.
  • Fengran Mo, Longxiang Zhao, Kaiyu Huang, Yue Dong, Degen Huang, Jian-Yun Nie. How to Leverage Personal Textual Knowledge for Personalized Conversational Information Retrieval. In Proceedings of CIKM 2024.
  • Kaiyu Huang*, Fengran Mo*, Hongliang Li, You Li, Yuanchi Zhang, Weijian Yi, Yulong Mao, Jinchen Liu, Yuzhuang Xu, Jinan Xu, Jian-Yun Nie, Yang Liu. A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers. In arXiv Preprint 2024.
  • Fengran Mo, Bole Yi, Kelong Mao, Chen Qu, Kaiyu Huang, Jian-Yun Nie. ConvSDG: Session Data Generation for Conversational Search. In Companion Proceedings of WWW 2024.
  • Fengran Mo, Chen Qu, Kelong Mao, Tianyu Zhu, Zhan Su, Kaiyu Huang, Jian-Yun Nie. History-Aware Conversational Dense Retrieval. In Findings of ACL 2024.
  • Fengran Mo, Jian-Yun Nie, Kaiyu Huang, Kelong Mao, Yutao Zhu, Peng Li, Yang Liu. Learning to Relate to Previous Turns in Conversational Search. In Proceedings of SIGKDD 2023 (Oral).
  • Fengran Mo, Kelong Mao, Yutao Zhu, Yihong Wu, Kaiyu Huang, Jian-Yun Nie. ConvGQR: Generative Query Reformulation for Conversational Search. In Proceedings of ACL 2023 (Oral).
  • Huimin Chen*, Fengran Mo*, Yanhao Wang, Cen Chen, Jian-Yun Nie, Chengyu Wang, Jamie Cui. A Customized Text Sanitization Mechanism with Differential Privacy. In Findings of ACL 2023.
  • Zhan Su, Fengran Mo, Prayag Tiwari, Benyou Wang, Qiuchi Li, Jian-Yun Nie, Jakob Grue Simonsen. Mixture of Latent Experts Using Tensor Products. Transactions on Machine Learning Research (TMLR) 2024.
  • Jiayin Wang, Fengran Mo, Weizhi Ma, Peijie Sun, Min Zhang, Jian-Yun Nie. A User-Centric Multi-Intent Benchmark for Evaluating Large Language Models. In Proceedings of EMNLP 2024. [Resource Award] (Only two)
  • Kelong Mao, Chenlong Deng, Haonan Chen, Fengran Mo, Zheng Liu, Tetsuya Sakai, Zhicheng Dou. ChatRetriever: Adapting Large Language Models for Generalized and Robust Conversational Dense Retrieval. In Proceedings of EMNLP 2024.
  • Kelong Mao, Zheng Liu, Hongjin Qian, Fengran Mo, Chenlong Deng, Zhicheng Dou. RAG-Studio: Towards In-Domain Adaptation Of Retrieval Augmented Generation Through Self-Alignment. In Findings of EMNLP 2024.
  • Yulong Mao, Kaiyu Huang, Changhao Guan, Baoling Gao, Fengran Mo, Jinan Xu. DoRA: Enhancing Parameter-Efficient Fine-Tuning with Dynamic Rank Distribution. In Proceedings of ACL 2024.
  • Yihong Wu, Le Zhang, Fengran Mo, Tianyu Zhu, Weizhi Ma, Jian-Yun Nie. Unifying Graph Convolution and Contrastive Learning in Collaborative Filtering. In Proceedings of SIGKDD 2024.
  • Tianyu Zhu, Yansong Shi, Yuan Zhang, Yihong Wu, Fengran Mo, Jian-Yun Nie. Collaboration and Transition: Distilling Item Transitions into Multi-Query Self-Attention for Sequential Recommendation. In Proceedings of WSDM 2024 (Oral).
  • Kelong Mao, Zhicheng Dou, Bang Liu, Hongjin Qian, Fengran Mo, Xiangli Wu, Xiaohua Cheng, Zhao Cao. Search-oriented Conversational Query Editing. In Findings of ACL 2023.
  • Kelong Mao, Hongjin Qian, Fengran Mo, Zhicheng Dou, Bang Liu, Xiaohua Cheng, Zhao Cao. Learning Denoised and Interpretable Session Representation for Conversational Search. In Proceedings of WWW 2023. [Spotlight-Best Paper Award Nominations]
  • Kelong Mao, Zhicheng Dou, Fengran Mo, Haonan Chen, Hongjin Qian, Jiewen Hou. Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Search. In Findings of EMNLP 2023.
  • Le Zhang, Yihong Wu, Fengran Mo, Jian-Yun Nie, Aishwarya Agrawal. MOQA: Zero-Shot Multi-modal Open-domain Question Answering. In Findings of EMNLP 2023.
  • Kelong Mao, Zhicheng Dou, Hongjin Qian, Fengran Mo, Xiaohua Cheng, Zhao Cao. ConvTrans: Transforming Web Search Sessions for Conversational Dense Retrieval. In Proceedings of EMNLP 2022.
  • Kaiyu Huang, Keli Xiao, Fengran Mo, Bo Jin, Zhuang Liu, Degen Huang. Domain-Aware Word Segmentation for Chinese Language: A Document-Level Context-Aware Model. TALLIP (2021).
  • Kaiyu Huang, Degen Huang, Zhuang Liu Fengran Mo. A Joint Multiple Criteria Model in Transfer Learning for Cross-domain Chinese Word Segmentation. In Proceedings of EMNLP 2020.