Kelong Mao (毛科龙) CS/IR/NLP Ph.D. Candidate Renmin University of China [Google Scholar] [DBLP] [GitHub] [Linkedin]

About

I am a fourth-year Ph.D. student at the Gaoling School of Artificial Intelligence, Renmin University of China. I am fortunate to be advised by Prof. Zhicheng Dou. Previously, I received M.Eng and B.Eng degrees in Computer Science from Tsinghua University in 2021 and from Nankai University in 2018, respectively.

I am working on generative information retrieval and LLMs.

News

• [Nov. 2024] One paper about long-context LLMs was accepted by KDD 2025.
• [Sept. 2024] Check out our new RAG framework: MemoRAG – transforming RAG with super-long memory for smarter, more accurate, and global-aware responses.
• [Sept. 2024] Five papers were accepted by EMNLP 2024 (3 Main and 2 Findings)! Thanks to all co-authors.
• [July 2024] We release our technical report of Yulan-12B.
• [May. 2024] Five papers were accepted by ACL 2024 (3 Main and 2 Findings)! Thanks to all co-authors.
• [Oct. 2023] One paper about leveraging LLM for conversational search was accepted by EMNLP 2023!
• [July. 2023] Start applied scientist intern in Amazon Seattle!
• [May. 2023] One paper about conversational search was accepted by KDD 2023.
• [May. 2023] Two papers about conversational search were accepted by ACL 2023.

Research Experiences

• Amazon Fashion, Applied Scientist Intern. Aug 2024 - Nov. 2024, Seattle, USA
• Waseda University, Visiting Research Fellow. Jan. 2024 - June. 2024, Tokyo, Japan
• Amazon Ads, Applied Scientist Intern. Jul 2023 - Oct. 2023, Seattle, USA
• Bytedance, Tiktok Search, Research Engineer Intern. Jan. 2021 - Jun. 2021, Beijing, China
• Tencent AI Lab, Research Intern. Jul. 2019 - Dec. 2019, Shenzhen, China

Publications & Preprints

(* denotes equal contributions)

• Tackling the Length Barrier: Dynamic Context Browsing for Knowledge-intensive Task
  Hongjin Qian, Zheng Liu, Peitian Zhang, Kelong Mao, Yujia Zhou, Xu Chen, Zhicheng Dou.
  KDD 2025. [Paper]

• MemoRAG: Moving towards Next-Gen RAG Via Memory-Inspired Knowledge Discovery.
  Hongjin Qian, Peitian Zhang, Zheng Liu, Kelong Mao, Zhicheng Dou.
  Arxiv 2024. [Paper] [Code]

• ChatRetriever: Adapting Large Language Models for Generalized and Robust Conversational Dense Retrieval.
  Kelong Mao, Chenlong Deng, Haonan Chen, Fengran Mo, Zheng Liu, Tetsuya Sakai, Zhicheng Dou.
  EMNLP 2024. [Paper]

• RAG-Studio: Towards In-Domain Adaptation Of Retrieval Augmented Generation Through Self Alignment
  Kelong Mao, Zheng Liu, Hongjin Qian, Fengran Mo, Chenlong Deng, Zhicheng Dou
  EMNLP 2024 (Findings).

• YuLan: An Open-source Large Language Model
  Yutao Zhu, Kun Zhou, Kelong Mao, Wentong Chen, Yiding Sun, Zhipeng Chen, Qian Cao, Yihan Wu, Yushuo Chen, Feng Wang, Lei Zhang, Junyi Li, Xiaolei Wang, Lei Wang, Beichen Zhang, Zican Dong, Xiaoxue Cheng, Yuhan Chen, Xinyu Tang, Yupeng Hou, Qiangqiang Ren, Xincheng Pang, Shufang Xie, Wayne Xin Zhao, Zhicheng Dou, Jiaxin Mao, Yankai Lin, Ruihua Song, Jun Xu, Xu Chen, Rui Yan, Zhewei Wei, Di Hu, Wenbing Huang, Ze-Feng Gao, Yueguo Chen, Weizheng Lu, and Ji-Rong Wen
  Technical Report 2024. [Paper]

• Enabling Discriminative Reasoning in LLMs for Legal Judgment Prediction
  Chenlong Deng, Kelong Mao, Yuyao Zhang, Zhicheng Dou
  EMNLP 2024 (Findings).

• Learning Interpretable Legal Case Retrieval via Knowledge-Guided Case Reformulation
  Chenlong Deng, Kelong Mao, Zhicheng Dou
  EMNLP 2024.

• CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Search
  Fengran Mo, Abbas Ghaddar, Kelong Mao, Mehdi Rezagholizadeh, Boxing Chen, Qun Liu, Jian-Yun Nie.
  EMNLP 2024. [Paper]

• Interpreting Conversational Dense Retrieval by Rewriting-Enhanced Inversion of Session Embedding.
  Yiruo Cheng, Kelong Mao, Zhicheng Dou.
  ACL 2024. [Paper]

• Grounding Language Model with Chunking-Free In-Context Retrieval.
  Hongjin Qian, Zheng Liu, Kelong Mao, Yujia Zhou, Zhicheng Dou.
  ACL 2024. [Paper]

• Generalizing Conversational Dense Retrieval via LLM-Cognition Data Augmentation.
  Haonan Chen, Zhicheng Dou, Kelong Mao, Jiongnan Liu, Ziliang Zhao.
  ACL 2024. [Paper]

• An Element is Worth a Thousand Words: Enhancing Legal Case Retrieval by Incorporating Legal Elements.
  Chenlong Deng, Zhicheng Dou, Yujia Zhou, Peitian Zhang, Kelong Mao.
  ACL 2024 Findings.

• History-Aware Conversational Dense Retrieval.
  Fengran Mo, Chen Qu, Kelong Mao, Tianyu Zhu, Zhan Su, Kaiyu Huang, Jian-Yun Nie.
  ACL 2024 Findings. [Paper]

• ConvSDG: Session Data Generation for Conversational Search.
  Fengran Mo, Bole Yi, Kelong Mao, Chen Qu, Kaiyu Huang and Jian-Yun Nie.
  WWW 2024 Workshop: Information Retrieval Meets Large Language Models

• Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Search.
  Kelong Mao, Zhicheng Dou, Fengran Mo, Jiewen Hou, Haonan Chen, Hongjin Qian.
  Findings of EMNLP 2023.

• Learning to Relate to Previous Turns in Conversational Search.
  Fengran Mo, Jian-Yun Nie, Kaiyu Huang, Kelong Mao, Yutao Zhu, Peng Li, Yang Liu
  KDD 2023.

• ConvGQR: Generative Query Reformulation for Conversational Search.
  Fengran Mo, Kelong Mao, Yutao Zhu, Yihong Wu, Kaiyu Huang and Jian-Yun Nie
  ACL 2023.

• Search-oriented Conversational Query Editing.
  Kelong Mao, Zhicheng Dou, Bang Liu, Hongjin Qian, Fengran Mo, Xiangli Wu, Xiaohua Cheng and Zhao Cao
  Findings of ACL 2023.

• Learning Denoised and Interpretable Session Representation for Conversational Search.
  Kelong Mao, Hongjin Qian, Fengran Mo, Zhicheng Dou, Bang Liu, Xiaohua Cheng, Zhao Cao.
  WWW 2023. [Spotlight-Best Paper Award Nominations, 16 out of 365 accepted papers] [Paper] [Code]

• FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction.
  Kelong Mao*, Jieming Zhu*, Liangcai Su, Guohao Cai, Yuru Li, Zhenhua Dong.
  AAAI 2023. [Paper] [Code]

• ConvTrans: Transforming Web Search Sessions for Conversational Dense Retrieval.
  Kelong Mao, Zhicheng Dou, Hongjin Qian, Fengran Mo, Xiaohua Cheng, Zhao Cao.
  EMNLP 2022. [Paper][Code]

• Curriculum Contrastive Context Denoising for Few-shot Conversational Dense Retrieval.
  Kelong Mao, Zhicheng Dou, Hongjin Qian.
  SIGIR 2022. [Paper][Code]

• UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation.
  Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He.
  CIKM 2021. [Paper][Code]

• SimpleX:A Simple and Strong Baseline for Collaborative Filtering.
  Kelong Mao*, Jieming Zhu*, Jinpeng Wang, Quanyu Dai, Zhenhua Dong, Xi Xiao, Xiuqiang He.
  CIKM 2021. [Paper][Code]

• Byte-Label Joint Attention Learning for Network Traffic Classification.
  Kelong Mao, Xi Xiao, Guangwu Hu, Xiapu Luo, Bin Zhang, Shutao Xia.
  IWQoS 2021. [Paper]

• Molecular Graph Enhanced Transformer for Retrosynthesis Prediction.
  Kelong Mao, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang, Peilin Zhao.
  Journal of Neurocomputing, 2021. [Paper][Code]

• Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach.
  Kelong Mao, Xi Xiao, Jieming Zhu, Biao Lu, Ruiming Tang, Xiuqiang He.
  SIGIR 2020. [Paper][Code]

Awards

• Best Paper Award Nominations of The Web Conference (WWW), 2023. (16 out of 365 accepted papers)
• National Scholarship for Doctoral Students, Renmin University of China, 2022 & 2023 (Two times).
• ACM SIGIR 2022 Student Travel Grant.
• Comprehensive Excellent First-class Scholarship, Tsinghua University, 2020.