I am a 4th-year PhD candidate in School of Intelligence Science and Technology at Peking University, working with Prof. Y. Zhang. I obtained my bachelor’s degree from the School of Computer Science and Engineering, UESTC in June 2021, under the supervision of Prof. K. Zheng. I’ve also spent time at Tongyi Lab, Baidu Reserch, MSRA, DAMO Academy and Huawei.
My current research interests include RAG, Agent and LLMs. If you are also interested, please feel free to drop me an email.
🔥 News
- 2024.09: 🎉🎉 My paper entitled “Towards Verifiable Text Generation with Evolving Memory and Self-Reflection” was accepted by EMNLP 2024!
- 2024.09: 🎉🎉 My paper entitled “Retrieved In-Context Principles from Previous Mistakes” was accepted by EMNLP 2024!
- 2024.09: 🎉🎉 My paper entitled “AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning” was accepted by EMNLP 2024!
- 2024.04: 🎉🎉 Nominated for the Academic Star Award!
- 2023.12: 🎉🎉 My paper entitled “Towards Verifiable Text Generation with Evolving Memory and Self-Reflection” is available on Arxiv!
- 2023.10: 🎉🎉 My paper entitled “LEAD: Liberal Feature-based Distillation for Dense Retrieval” was accepted by WSDM 2024!
- 2023.10: 🎉🎉 My paper entitled “Allies: Prompting Large Language Model with Beam Search” was accepted by EMNLP 2023!
- 2023.08: 🎉🎉 Awarded as Stars of Tomorrow during an internship at Microsoft!
📝 Publications

Towards Verifiable Text Generation with Evolving Memory and Self-Reflection
Hao Sun, H. Cai, B. Wang, Y. Hou, X. Wei, S. Wang, Y. Zhang, D. Yin
The Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Improving citation generation with a two-tier verifier and active retrieval mechanism.

Retrieved In-Context Principles from Previous Mistakes
Hao Sun, Y. Jiang, B. Wang, Y. Hou, Y. Zhang, P. Xie, F. Huang
The Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Enabling LLMs to learn from mistakes by providing question-level and task-level principles.

Hao Sun, J. Wu, H. Cai, X. Wei, Y. Feng, B. Wang, S. Wang, Y. Zhang, D. Yin
The Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Enabling adaptive switching between local agent and cloud agent through collaborative learning.

LEAD: Liberal Feature-based Distillation for Dense Retrieval
Hao Sun, X. Liu, Y. Gong, A. Dong, J. Lu, Y. Zhang, L. Yang, R. Majumder, N. Duan
The ACM International Conference on Web Search and Data Mining (WSDM), 2024, Oral
Distilling the intermediate features from teacher to student without the constraints on model architecture or tokenizers.

Allies: Prompting Large Language Model with Beam Search
Hao Sun, X. Liu, Y. Gong, Y. Zhang, N. Duan
The Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023, Findings
Improving the knowledge scope and robustness of LLMs with Beam Search.

History Semantic Graph Enhanced Conversational KBQA with Temporal Information Modeling
Hao Sun, Y.g Li, L. Deng, B. Li, B. Hui, B. Li, Y. Lan, Y. Zhang, Y. Li
The Annual Meeting of the Association for Computational Linguistics (ACL), 2023
Modeling history conversation information with History Semantic Graph.

Hao Sun, Y. Li, Y. Zhang
The SIAM International Conference on Data Mining (SDM), 2022
Capturing complex transition patterns between concepts through Graph Neural Network.

PeriodicMove: Shift-aware Human Mobility Recovery with Graph Neural Network
Hao Sun, C. Y.g, L. Deng, F. Zhou, F. Huang, K. Zheng
The ACM International Conference on Information and Knowledge Management (CIKM), 2021
Capturing multi-level periodicity and shifting periodicity of human mobility using attention mechanism.

Personalized Dynamic Knowledge-Aware Recommendation with Hybrid Explanations
Hao Sun, Z. Wu, Y. Cui, L. Deng, Y. Zhao, K. Zheng
The International Conference on Database Systems for Advanced Applications (DASFAA), 2021
Providing personalized and hybrid explanations for the recommendations.

Cross-model Control: Improving Multiple Large Language Models in One-time Training
J. Wu, Hao Sun, H Cai, L Su, S Wang, D Yin, X Li, M Gao
The Annual Conference on Neural Information Processing Systems (NeurIPS), 2024
Improves multiple LLMs in one-time training with a portable tiny language model.

A Neural Corpus Indexer for Document Retrieval
Y. Wang, Y. Hou, H. Wang, Z. Miao, S. Wu, Hao Sun, Q. Chen, Y. Xia, C. Chi, G. Zhao, Z. Liu, X. Xie, H. Allen Sun, W. Deng, Q. Zhang, M. Yang
The Annual Conference on Neural Information Processing Systems (NeurIPS), 2024
Propose an end-to-end differentiable document retrieval model that can significantly outperform both inverted index and dense retrieval solutions.

PA-RAG: RAG Alignment via Multi-Perspective Preference Optimization
J. Wu, H. Cai, L. Yan, Hao Sun, X. Li, S. Wang, D. Yin, M. Gao
The Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL), 2025
Optimizing the RAG generator to align with RAG requirements comprehensively.

Sequential-Knowledge-Aware Next POI Recommendation: A Meta-Learning Approach
Y. Cui, Hao Sun, Y. Zhao, H. Yin, K. Zheng
The ACM Transactions on Information Systems (TOIS), 2021
Utilize sequential, spatiotemporal, and social knowledge to recommend the next POI for a location-based social network user.

Robust domain misinformation detection via multi-modal feature alignment
H. Liu, W. Wang, H. Sun, A. Rocha, H. Li
IEEE Transactions on Information Forensics and Security (TIFS), 2024
Propose a novel robust domain and cross-modal approach (RDCM) for multi-modal misinformation detection.

S2TUL: A Semi-Supervised Framework for Trajectory-User Linking
L. Deng, Hao Sun, Y. Zhao, S. Liu, K. Zheng
The ACM International Conference on Web Search and Data Mining (WSDM), 2023
Capture fine-grained intra-trajectory information by passing the trajectories into the sequential neural networks.

Efficient Trajectory Similarity Computation with Contrastive Learning
L. Deng, Y. Zhao, Z. Fu, Hao Sun, S. Liu, K. Zheng
The ACM International Conference on Information and Knowledge Management (CIKM), 2022
Employ a contrastive learning mechanism to learn the representations of trajectories, which are then used to calculate the dissimilarity between them.

Efficient and Effective Similar Subtrajectory Search: A Spatial-aware Comprehension Approach
L. Deng, Hao Sun, R. Sun, Y. Zhao, H. Su
The ACM Transactions on Intelligent Systems and Technology (TIST), 2022
Propose a Similar Subtrajectory Search with a Graph Neural Networks framework.

Fusing Local and Global Mobility Patterns for Trajectory Recovery
L. Deng, Y. Zhao, Hao Sun, C. Yang, J. Xie, K. Zheng
The ACM International Conference on Information and Knowledge Management (CIKM), 2022
Propose a neural attention model based on graph convolutional networks to enhance the accuracy of trajectory recovery.

Boosting Disfluency Detection with Large Language Model as Disfluency Generator
Z. Cheng, J. Guo, Hao Sun, Y. Zhang
The IEEE International Conference on Multimedia & Expo (ICME), 2024
Propose a framework that addresses data sparsity issues by generating disfluent data using LLM as augmentation data.
📒 Preprint

SimCNS: Simple Curriculum Negative Sampling for Multi-Source Dense Retrieval
Hao Sun, X. Liu, Y. Gong, A. Dong, G. Shi, Y. Zhang, L. Yang, N. Duan
Arxiv, 2024
Improving multi-source dense retrieval with Curriculum Negative Sampling.
🎖 Honors and Awards
- 2024.06 First Prize of Challenge Cup Competition, Peking University.
- 2024.03 Academic Star Nomination.
- 2023.09 Merit Student of Peking University.
- 2023.09 Schlumberger Scholarship.
- 2023.08 Stars of Tomorrow Award at Microsoft, Microsoft.
- 2023.06 First Prize of Challenge Cup Competition, Peking University.
- 2022.12 Outstanding Paper Award, NeurIPS 2022.
- 2021.06 Outstanding Graduation Thesis for Undergraduates, UESTC.
- 2021.06 Outstanding Graduate, UESTC.
- 2019.12 National Scholarship.
- 2018.09 National Scholarship.
📖 Educations
- 2021.09 - Present, Ph.D. Candidate, Peking University.
- 2017.09 - 2021.06, Undergraduate, University of Electronic Science And Technology of China.
📚 Academic Services
- Program Committee / Reviewer: ARR 2022-25, NeurIPS 2024-2025, ICLR 2024-2025, ICML 2024-2025
- Secondary Reviewer: AAAI 2022, CIKM 2021-22, ICDM 2021-23, COLING 2022-23, DASFAA 2022-23
👩🏻🏫 Teaching
- Teaching Assistant, Computer Networks and Web Technologies, Peking University, Fall 2023
💻 Internships
- Tongyi Lab, focusing on Agent.
- Baidu Research, focusing on large language models.
- Microsoft Research Asia (MSRA), focusing on dense retrieval.
- DAMO Academy, focusing on multi-turn conversation.
- HUAWEI Research, focusing on spatial-temporal data analysis.