Runxue Bao

I am a Machine Learning Engineer at Google Search, where I work on personalized recommendation and AIGC quality for Search Discover and Notification, serving billions of users. I received my Ph.D. in Computer Engineering from the University of Pittsburgh and completed my Honours B.S. in Electrical Engineering at the University of Science and Technology of China.

Current interests & recent work include:

• Recommender Systems, Personalization, Retrieval and Ranking, Information Retrieval, GNN [NAACL 2024, MICCAI 2024]
• LLM-as-a-Judge/Rater, Parameter-Efficient Fine-Tuning (PEFT), Retrieval-Augmented Generation (RAG), and In-Context Learning (ICL) [NeurIPS 2025, EMNLP 2024, NAACL 2024 & 2025]
• Transfer Learning in Healthcare [ICHI 2023 & 2024, ISBI 2024, SDM 2025, AMIA 2025]
• Model Compression and Optimization [EMNLP 2025, NAACL 2024, CVPR 2024, ICML 2020, IJCAI 2022, CIKM 2022]

I’m open to collaboration opportunities—feel free to connect!

News

• [08/26] One paper on LLM Memorization was accepted by EMNLP 2026 Main Conference!
• [07/26] One survey paper on Heterogeneous Transfer Learning was accepted by Knowledge-Based Systems!
• [09/25] One paper on LLM-as-a-Judge was accepted by NeurIPS 2025!
• [08/25] One paper on LLM Memorization & Pruning was accepted by EMNLP 2025 Main Conference!
• [05/25] One paper on Sparse Optimization was accepted by ECML PKDD 2025!
• [03/25] One paper on Sparse Optimization was accepted by IJCNN 2025!
• [01/25] One paper on Retrieval-Augmented In-Context Learning was accepted by NAACL 2025 Main Conference!
• [12/24] One paper on Temporal Domain Adaptation was accepted by SDM 2025!
• [11/24] One paper on LLMs & Transfer Learning was accepted by AMIA 2025 Informatics Summit!
• [09/24] Two papers on LLMs were accepted by EMNLP 2024! One focuses on Estimating LLM Memorization and the other explores Enhancing LLMs with Knowledge Graphs!
• [06/24] One paper on Online Transfer Learning received ICHI 2024 Best Paper Award (Analytics Track)!
• [05/24] One paper on Graph Neural Network was accepted by MICCAI 2024!
• [03/24] One paper on LLM Pruning was accepted by NAACL 2024!
• [03/24] One paper on Online Transfer Learning was accepted by IEEE ICHI 2024!
• [02/24] One paper on Model Compression was accepted by CVPR 2024!
• [01/24] Two papers on Transfer Learning and Multimodal Learning were accepted by ISBI 2024!
• [10/23] One survey paper on Heterogeneous Transfer Learning was on arXiv!
• [08/23] One paper on Online Pairwise Learning was accepted by IEEE TNNLS 2023!

Selected Publications

• Any Large Language Model Can Be a Reliable Judge: Debiasing with a Reasoning-based Bias Detector
  Haoyan Yang, Runxue Bao, Cao Xiao, Jun Ma, Parminder Bhatia, Shangqian Gao, Taha Kass-Hout.
  NeurIPS 2025
• Controllable Memorization in LLMs via Weight Pruning
  Chenjie Ni, Zhepeng Wang, Runxue Bao, Shangqian Gao, Yanfu Zhang.
  EMNLP 2025 - Main
• Dynamic Uncertainty Ranking: Enhancing In-Context Learning for Long-Tail Knowledge in LLMs [Paper]
  Shuyang Yu, Runxue Bao, Parminder Bhatia, Taha Kass-Hout, Jiayu Zhou, Cao Xiao.
  NAACL 2025 - Main
• Domain-Adaptive Continual Meta-Learning for Modeling Dynamical Systems: An Application in Environmental Ecosystems
  Yiming Sun, Runlong Yu, Runxue Bao, Yiqun Xie, Ye Ye and Xiaowei Jia.
  SDM 2025
• Unlocking Memorization in Large Language Models with Dynamic Soft Prompting [Paper]
  Zhepeng Wang, Runxue Bao, Yawen Wu, Jackson Taylor, Cao Xiao, Feng Zheng, Weiwen Jiang, Shangqian Gao, Yanfu Zhang.
  EMNLP 2024 - Main
• InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integration [Paper]
  Fali Wang, Runxue Bao, Suhang Wang, Wenchao Yu, Yanchi Liu, Wei Cheng, Haifeng Chen.
  EMNLP 2024 Findings
• Self-guided Knowledge-injected Graph Neural Network for Alzheimer’s Diseases [Paper]
  Zhepeng Wang, Runxue Bao, Yawen Wu, Guodong Liu, Lei Yang, Liang Zhan, Feng Zheng, Weiwen Jiang, Yanfu Zhang.
  MICCAI 2024
• Pruning as a Domain-specific LLM Extractor [Paper]
  Nan Zhang, Yanchi Liu, Xujiang Zhao, Wei Cheng, Runxue Bao, Rui Zhang, Prasenjit Mitra, Haifeng Chen.
  NAACL 2024 Findings
• Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch [Paper]
  Xidong Wu, Shangqian Gao, Zeyu Zhang, Zhenzhen Li, Runxue Bao, Yanfu Zhang, Xiaoqian Wang, Heng Huang.
  CVPR 2024
• Neurodegenerative Disease Prediction via Transferable Deep Networks [Paper]
  Yanfu Zhang, Guodong Liu, Runxue Bao, Liang Zhan, Paul Thompson, Heng Huang.
  ISBI 2024
• Brain Image Synthesis Using Incomplete Multimodal Data [Paper]
  Yanfu Zhang, Guodong Liu, Runxue Bao, Liang Zhan, Paul Thompson, Heng Huang.
  ISBI 2024
• Online Transfer Learning for RSV Case Detection [Paper]
  Yiming Sun, Yuhe Gao, Runxue Bao, Gregory F Cooper, Jessi Espino, Harry Hochheiser, Marian G Michaels, John M Aronis, Ye Ye.
  ICHI 2024 (Best Paper Award)
• A Survey of Heterogeneous Transfer Learning [Paper]
  Runxue Bao*, Yiming Sun*, Yuhe Gao, Jindong Wang, Qiang Yang, Haifeng Chen, Zhi-Hong Mao, Ye Ye.
  arXiv 2023
• New Scalable and Efficient Online Pairwise Learning Algorithm [Paper]
  Bin Gu, Runxue Bao, Chenkang Zhang, Heng Huang.
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS 2023)
• Prediction of COVID-19 Patients’ Emergency Room Revisit using Multi-Source Transfer Learning [Paper]
  Yuelyu Ji*, Yuhe Gao*, Runxue Bao*, Qi Li, Disheng Liu, Yiming Sun, and Ye Ye. (* denotes equal contribution)
  ICHI 2023
• An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification [Paper] [Slides]
  Runxue Bao, Bin Gu, Heng Huang.
  CIKM 2022
• Doubly Sparse Asynchronous Learning for Stochastic Composite Optimization [Paper] [Slides]
  Runxue Bao, Xidong Wu, Wenhan Xian, Heng Huang.
  IJCAI 2022
• Toward Unified Data and Algorithm Fairness via Adversarial Data Augmentation and Adaptive Model Fine-tuning [Paper]
  Yanfu Zhang, Runxue Bao, Jian Pei, Heng Huang.
  ICDM 2022
• Fast OSCAR and OWL Regression via Safe Screening Rules [Paper] [Code] [Slides]
  Runxue Bao, Bin Gu, Heng Huang.
  ICML 2020

Services

• Conference Program Committee or Reviewer:
  • 2025: ICLR, AAAI, AISTATS, WACV
  • 2024: ICML, ICLR, NeurIPS, NeurIPS Datasets and Benchmarks Track, CVPR, ACL ARR, ECCV, AAAI, IJCAI, WACV, WSDM (PC), SDM, IEEE CAI, AutoML, LOG
  • 2023: ICLR, ICML, NeurIPS, NeurIPS Datasets and Benchmarks Track, KDD (PC), IJCAI (PC), ECAI, WACV, AMIA, IEEE CEC, FUZZ-IEEE, AutoML, LOG
  • 2022: ICML, NeurIPS, NeurIPS Datasets and Benchmarks Track, ICLR, AISTATS, IEEE WCCI, LOG
  • 2021: ICML, NeurIPS
  • 2020: KDD (PC), MLSP
  • 2019: MLSP
• Journal Reviewer:
  • Briefings in Bioinformatics
  • Artificial Intelligence in Medicine
  • IEEE Transactions on Big Data
  • Patterns
  • Knowledge and Information Systems (KAIS)
  • Journal of Combinatorial Optimization
  • IEEE Open Journal of the Computer Society (OJCS)