Publications

Core Works

LLM Knowledge Boundary Perception

• How Long Reasoning Chains Influence LLMs’ Judgment of Answer Factuality[Arxiv] [Code]
  Minzhu Tu=, Shiyu Ni= and Keping Bi
  ACL’ 2026: The 64th Annual Meeting of the Association for Computational Linguistics
• Annotation-Efficient Universal Honesty Alignment[Arxiv] [Code]
  Shiyu Ni, Keping Bi, Jiafeng Guo, Minghao Tang, Jingtong Wu, Zengxin Han and Xueqi Cheng
  ICLR’ 2026: The Fourteenth International Conference on Learning Representations
• Towards Fully Exploiting LLM Internal States to Enhance Knowledge Boundary Perception[Arxiv] [Code] [Poster]
  Shiyu Ni, Keping Bi, Jiafeng Guo, Lulu Yu, Baolong Bi and Xueqi Cheng
  ACL’ 2025: The 63rd Annual Meeting of the Association for Computational Linguistics
• When Do LLMs Need Retrieval Augmentation? Mitigating LLMs’ Overconfidence Helps Retrieval Augmentation[Arxiv] [Blog] [Code]
  Shiyu Ni, Keping Bi, Jiafeng Guo and Xueqi Cheng
  ACL’ 2024: Findings of the Association for Computational Linguistics, 2024
• Are Large Language Models More Honest in Their Probabilistic or Verbalized Confidence?[Arxiv]
  Shiyu Ni, Keping Bi, Lulu Yu and Jiafeng Guo
  CCIR’ 2024: The 30th China Conference on Information Retrieval
• Do LVLMs Know What They Know? A Systematic Study of Knowledge Boundary Perception in LVLMs[Arxiv] [Code]
  Zhikai Ding, Shiyu Ni, and Keping Bi
  EMNLP’ 2025: Findings of Empirical Methods in Natural Language Processing
  Propose the idea and refine the whole paper.
• How Knowledge Popularity Influences and Enhances LLM Knowledge Boundary Perception[Arxiv]
  Shiyu Ni, Keping Bi, Jiafeng Guo and Xueqi Cheng
  
• Evaluating and Calibrating LLM Confidence on Questions with Multiple Correct Answers[Arxiv] [Code]
  Yuhan Wang=, Shiyu Ni=, Zhikai Ding, Zihang Zhan, Yuanzi Li and Keping Bi
  

Clarifying Question Generation/Facet Generation

• A Comparative Study of Training Objectives for Clarification Facet Generation[PDF] [Code] [PPT]
  Shiyu Ni, Keping Bi, Jiafeng Guo and Xueqi Cheng
  SIGIR-AP’ 2023: Proceedings of the 1st International ACM SIGIR Conference on Information Retrieval in the Asia Pacific

Knowledge Utilization

• Injecting External Knowledge into the Reasoning Process Enhances Retrieval-Augmented Generation[Arxiv] [Code]
  Minghao Tang, Shiyu Ni, Jiafeng Guo and Keping Bi
  SIGIR-AP’ 2025: Proceedings of the 3rd International ACM SIGIR Conference on Information Retrieval in the Asia Pacific
  Write abstract, introduction, refine the whole paper and conduct experimental analysis
• The Role of Parametric Injection-A Systematic Study of Parametric Retrieval-Augmented Generation[Arxiv]
  Minghao Tang, Shiyu Ni, Jingtong Wu, Zengxin Han and Keping Bi
  Write abstract, introduction and refine the whole paper (Version 1)

Collaborations

• Is Factuality Enhancement a Free Lunch For LLMs? Better Factuality Can Lead to Worse Context-Faithfulness[Arxiv]
  Baolong Bi, Shenghua Liu, Yiwei Wang, Lingrui Mei, Junfeng Fang, Hongcheng Gao, Shiyu Ni and Xueqi Cheng
  ICLR’ 2025: The Thirteenth International Conference on Learning Representations
• Deep Research: A Systematic Survey[Arxiv] [Repo]
  Zhengliang Shi, Yiqun Chen, Haitao Li, Weiwei Sun, Shiyu Ni, Yougang Lyu, Runze Fan et.al.
  Preprint 2025
  Write Section 3.2.2 and Section 6.1.