Ming Li, Pei Chen, Zhenhao Zhang, Tao Yang, Xinyang Zhang, Han Li, Tianyu Cao, Ming Zeng, Zhuofeng Wu, Meng Jiang, Huasheng Li, Lihong Li, Bing Yin. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

Multi-turn interactions between users and information-seeking systems have become a popular paradigm to satisfy complex information needs via a flexible interface and context understanding capacity. However, existing methods primarily adapt single-turn retrieval-augmented generation (RAG) pipelines to conversational settings without effectively incorporating historical information, such as previous search results, turn dependency, and historical evidence grounding. To effectively manage and utilize the information in conversations, we explore the feasibility of boosting response generation by leveraging historical information and propose several strategies to incorporate this information individually or in combination. We conduct experiments on three widely used conversational search benchmarks, each containing thousands of samples. Our method consistently outperforms previous strong baselines across different settings, achieving approximately a 10% absolute improvement over the second-best approach. Besides, our analyses help to understand the behind-the-scenes behavior of our methods. • We investigate the feasibility of leveraging abundant historical information to improve RAG performance in conversations. • We design several training-free strategies from different aspects, that can be used individually or in combination to boost RAG performance. • We conduct thorough experiments on three datasets to demonstrate the effectiveness of our methods, and analyze the potential paradigms behind the model.

Fengran Mo, Yifan Gao, Chuan Meng, Xin Liu, Zhuofeng Wu, Kelong Mao, Zhengyang Wang, Pei Chen, Zheng Li, Xian Li, Bing Yin, Meng Jiang. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025.

Hy Dang, Tianyi Liu, Zhuofeng Wu, Jingfeng Yang, Haoming Jiang, Tao Yang, Pei Chen, Zhengyang Wang, Helen Wang, Huasheng Li, Bing Yin, Meng Jiang. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. 2025.