Peiyang Liu

According to our database, Peiyang Liu authored at least 24 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Looking Farther with Confidence: Uncertainty-Guided Future Learning for Sequential Recommendation.

Ziqiang Cui, Xing Tang, Peiyang Liu, Xiaokun Zhang, Shiwei Li, Xiuqiang He, Chen Ma

CoRR, May, 2026

Beyond Semantic Relevance: Counterfactual Risk Minimization for Robust Retrieval-Augmented Generation.

Peiyang Liu, Qiang Yan, Ziqiang Cui, Di Liang, Xi Wang, Wei Ye

CoRR, May, 2026

Chain of Evidence: Pixel-Level Visual Attribution for Iterative Retrieval-Augmented Generation.

Peiyang Liu, Ziqiang Cui, Xi Wang, Di Liang, Wei Ye

CoRR, May, 2026

Parameter Importance is Not Static: Evolving Parameter Isolation for Supervised Fine-Tuning.

Zekai Lin, Chao Xue, Di Liang, Xingsheng Han, Peiyang Liu, Xianjie Wu, Lei Jiang, Yu Lu, Haibo Shi, Shuang Liang, Minlong Peng

CoRR, April, 2026

Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty.

Chao Xue, Yao Wang, Mengqiao Liu, Di Liang, Xingsheng Han, Peiyang Liu, Xianjie Wu, Chenyao Lu, Lei Jiang, Yu Lu, Haibo Shi, Shuang Liang, Minlong Peng, Flora D. Salim

CoRR, April, 2026

StructKV: Preserving the Structural Skeleton for Scalable Long-Context Inference.

Zhirui Chen, Peiyang Liu, Ling Shao

CoRR, April, 2026

SQL-ASTRA: Alleviating Sparse Feedback in Agentic SQL via Column-Set Matching and Trajectory Aggregation.

Long Li, Zhijian Zhou, Jiangxuan Long, Peiyang Liu, Weidi Xu, Zhe Wang, Shirui Pan, Chao Qu

CoRR, March, 2026

ToolSafe: Enhancing Tool Invocation Safety of LLM-based agents via Proactive Step-level Guardrail and Feedback.

Yutao Mou, Zhangchi Xue, Lijun Li, Peiyang Liu, Shikun Zhang, Wei Ye, Jing Shao

CoRR, January, 2026

Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models.

Chao Xue, Yao Wang, Mengqiao Liu, Di Liang, Xingsheng Han, Peiyang Liu, Xianjie Wu, Chenyao Lu, Lei Jiang, Yu Lu, Haibo Shi, Shuang Liang, Minlong Peng, Flora D. Salim

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

Learning from Contrasts: Synthesizing Reasoning Paths from Diverse Search Trajectories.

Peiyang Liu, Zhirui Chen, Xi Wang, Di Liang, Youru Li, Zhi Cai, Wei Ye

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

Parameter Importance is Not Static: Evolving Parameter Isolation for Supervised Fine-Tuning.

Zekai Lin, Chao Xue, Di Liang, Xingsheng Han, Peiyang Liu, Xianjie Wu, Lei Jiang, Yu Lu, Bob Simons, Shuang Liang, Minlong Peng

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

Who Stole Your Data? A Method for Detecting Unauthorized RAG Theft.

Peiyang Liu, Ziqiang Cui, Di Liang, Wei Ye

CoRR, October, 2025

CORE: Lossless Compression for Retrieval-Augmented LLMs via Reinforcement Learning.

Ziqiang Cui, Yunpeng Weng, Xing Tang, Peiyang Liu, Shiwei Li, Bowei He, Jiamin Chen, Xiuqiang He, Chen Ma

CoRR, August, 2025

Queries Are Not Alone: Clustering Text Embeddings for Video Search.

Peiyang Liu, Xi Wang, Ziqiang Cui, Wei Ye

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

Semantic Retrieval Augmented Contrastive Learning for Sequential Recommendation.

Ziqiang Cui, Yunpeng Weng, Xing Tang, Xiaokun Zhang, Shiwei Li, Peiyang Liu, Bowei He, Dugang Liu, Weihong Luo, Xiuqiang He, Chen Ma

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Structural Reward Model: Enhancing Interpretability, Efficiency, and Scalability in Reward Modeling.

Xiaoyu Liu, Di Liang, Hongyu Shan, Peiyang Liu, Yonghao Liu, Muling Wu, Yuntao Li, Xianjie Wu, Li Miao, Jiangrong Shen, Minlong Peng

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

2024

Unsupervised corrupt data detection for text training.

Peiyang Liu

Expert Syst. Appl., 2024

Efficient recognition of fish feeding behavior: A novel two-stage framework pioneering intelligent aquaculture strategies.

Kewei Cai, Zhipeng Yang, Tianyi Gao, Meng Liang, Peiyang Liu, Siyi Zhou, Hongshuai Pang, Ying Liu

Comput. Electron. Agric., 2024

2023

Retrieval-Based Unsupervised Noisy Label Detection on Text Data.

Peiyang Liu, Jinyu Yang, Lin Wang, Sen Wang, Yunlai Hao, Huihui Bai

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Label Smoothing for Text Mining.

Peiyang Liu, Xiangyu Xi, Wei Ye, Shikun Zhang

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

QuadrupletBERT: An Efficient Model For Embedding-Based Large-Scale Retrieval.

Peiyang Liu, Sen Wang, Xi Wang, Wei Ye, Shikun Zhang

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Improving Embedding-based Large-scale Retrieval via Label Enhancement.

Peiyang Liu, Xi Wang, Sen Wang, Wei Ye, Xiangyu Xi, Shikun Zhang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Distilling Knowledge from BERT into Simple Fully Connected Neural Networks for Efficient Vertical Retrieval.

Peiyang Liu, Xi Wang, Lin Wang, Wei Ye, Xiangyu Xi, Shikun Zhang

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Not All Synonyms Are Created Equal: Incorporating Similarity of Synonyms to Enhance Word Embeddings.

Peiyang Liu, Wei Ye, Xiangyu Xi, Tong Wang, Jinglei Zhang, Shikun Zhang

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020