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

About

I am a third-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 dedicated to developing advanced information distribution systems. My research covers information retrieval, conversational search, RAG, large language models, recommender systems, etc.

News

• [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 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)

• 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.
  Arxiv 2024. [Paper]

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

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

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

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