{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T02:12:08Z","timestamp":1765505528066,"version":"3.48.0"},"publisher-location":"New York, NY, USA","reference-count":29,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,10]]},"DOI":"10.1145\/3746252.3760903","type":"proceedings-article","created":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T00:36:36Z","timestamp":1762562196000},"page":"5330-5334","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["GenR1-Searcher: Curriculum Reinforcement Learning for Dynamic Retrieval and Document Generation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-7089-7991","authenticated-orcid":false,"given":"Yu","family":"Wang","sequence":"first","affiliation":[{"name":"Zhengzhou University, Zhengzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-1152-889X","authenticated-orcid":false,"given":"Yixuan","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6711-5020","authenticated-orcid":false,"given":"Renrui","family":"Duan","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9384-9455","authenticated-orcid":false,"given":"Jingyuan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6799-1756","authenticated-orcid":false,"given":"Yuanzhuo","family":"Wang","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-7984-1082","authenticated-orcid":false,"given":"Kun","family":"Zhang","sequence":"additional","affiliation":[{"name":"WeChat AI, Tencent Inc., Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,11,10]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Wenqi Fan Yujuan Ding Liangbo Ning Shijie Wang Hengyun Li Dawei Yin Tat-Seng Chua and Qing Li. 2024. A survey on rag meeting llms: Towards retrieval-augmented large language models. 6491-6501 pages.","DOI":"10.1145\/3637528.3671470"},{"key":"e_1_3_2_1_2_1","unstructured":"Yunfan Gao Yun Xiong Xinyu Gao Kangxiang Jia Jinliu Pan Yuxi Bi Yixin Dai Jiawei Sun Haofen Wang and Haofen Wang. 2023. Retrieval-augmented generation for large language models: A survey."},{"key":"e_1_3_2_1_3_1","unstructured":"Daya Guo Dejian Yang Haowei Zhang Junxiao Song Ruoyu Zhang Runxin Xu Qihao Zhu Shirong Ma Peiyi Wang Xiao Bi et al. 2025. Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning."},{"key":"e_1_3_2_1_4_1","volume-title":"Saku Sugawara, and Akiko Aizawa.","author":"Ho Xanh","year":"2020","unstructured":"Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, and Akiko Aizawa. 2020. Constructing a multi-hop qa dataset for comprehensive evaluation of reasoning steps."},{"key":"e_1_3_2_1_5_1","volume-title":"Jason Klein Liu, and Wei Shen","author":"Hu Jian","year":"2025","unstructured":"Jian Hu, Jason Klein Liu, and Wei Shen. 2025. Reinforce: An efficient rlhf algorithm with robustness to both prompt and reward models."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3703155"},{"key":"e_1_3_2_1_7_1","volume-title":"Big Progress or Bitter Lesson? arXiv preprint arXiv:2411.16489","author":"Huang Zhen","year":"2024","unstructured":"Zhen Huang, Haoyang Zou, Xuefeng Li, Yixiu Liu, Yuxiang Zheng, Ethan Chern, Shijie Xia, Yiwei Qin, Weizhe Yuan, and Pengfei Liu. 2024. O1 Replication Journey-Part 2: Surpassing O1-preview through Simple Distillation, Big Progress or Bitter Lesson? arXiv preprint arXiv:2411.16489 (2024)."},{"key":"e_1_3_2_1_8_1","unstructured":"Gautier Izacard and Edouard Grave. 2020. Distilling knowledge from reader to retriever for question answering."},{"key":"e_1_3_2_1_9_1","volume-title":"Atlas: Few-shot learning with retrieval augmented language models. 43 pages.","author":"Izacard Gautier","year":"2023","unstructured":"Gautier Izacard, Patrick Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, and Edouard Grave. 2023. Atlas: Few-shot learning with retrieval augmented language models. 43 pages."},{"key":"e_1_3_2_1_10_1","unstructured":"Aaron Jaech Adam Kalai Adam Lerer Adam Richardson Ahmed El-Kishky Aiden Low Alec Helyar Aleksander Madry Alex Beutel Alex Carney et al. 2024. Openai o1 system card."},{"key":"e_1_3_2_1_11_1","unstructured":"Bowen Jin Hansi Zeng Zhenrui Yue Jinsung Yoon Sercan Arik Dong Wang Hamed Zamani and Jiawei Han. 2025. Search-r1: Training llms to reason and leverage search engines with reinforcement learning."},{"key":"e_1_3_2_1_12_1","volume-title":"Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih.","author":"Karpukhin Vladimir","year":"2020","unstructured":"Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick SH Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020. Dense Passage Retrieval for Open-Domain Question Answering. 6769-6781 pages."},{"key":"e_1_3_2_1_13_1","unstructured":"Xiaoxi Li Guanting Dong Jiajie Jin Yuyao Zhang Yujia Zhou Yutao Zhu Peitian Zhang and Zhicheng Dou. 2025. Search-o1: Agentic search-enhanced large reasoning models."},{"key":"e_1_3_2_1_14_1","unstructured":"Xingxuan Li Weiwen Xu Ruochen Zhao Fangkai Jiao Shafiq Joty and Lidong Bing. 2024. Can We Further Elicit Reasoning in LLMs? Critic-Guided Planning with Retrieval-Augmentation for Solving Challenging Tasks."},{"key":"e_1_3_2_1_15_1","volume-title":"James Thorne, Yacine Jernite, Vladimir Karpukhin, Jean Maillard, et al.","author":"Petroni Fabio","year":"2020","unstructured":"Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vladimir Karpukhin, Jean Maillard, et al., 2020. KILT: a benchmark for knowledge intensive language tasks."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"Ofir Press Muru Zhang Sewon Min Ludwig Schmidt Noah A Smith and Mike Lewis. 2022. Measuring and narrowing the compositionality gap in language models.","DOI":"10.18653\/v1\/2023.findings-emnlp.378"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Zhihong Shao Yeyun Gong Yelong Shen Minlie Huang Nan Duan and Weizhu Chen. 2023. Enhancing retrieval-augmented large language models with iterative retrieval-generation synergy.","DOI":"10.18653\/v1\/2023.findings-emnlp.620"},{"key":"e_1_3_2_1_18_1","unstructured":"Zhongxiang Sun Qipeng Wang Weijie Yu Xiaoxue Zang Kai Zheng Jun Xu Xiao Zhang Song Yang and Han Li. 2025. ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Harsh Trivedi Niranjan Balasubramanian Tushar Khot and Ashish Sabharwal. 2022a. Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions.","DOI":"10.18653\/v1\/2023.acl-long.557"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Harsh Trivedi Niranjan Balasubramanian Tushar Khot and Ashish Sabharwal. 2022b. ? MuSiQue: Multihop Questions via Single-hop Question Composition. 539-554 pages.","DOI":"10.1162\/tacl_a_00475"},{"key":"e_1_3_2_1_21_1","unstructured":"Liang Wang Nan Yang Xiaolong Huang Binxing Jiao Linjun Yang Daxin Jiang Rangan Majumder and Furu Wei. 2022. Text embeddings by weakly-supervised contrastive pre-training."},{"key":"e_1_3_2_1_22_1","unstructured":"Ye Wang Xinrun Xu Rui Xie Wenxin Hu and Wei Ye. 2024. Generative Retrieval with Large Language Models."},{"key":"e_1_3_2_1_23_1","volume-title":"Denny Zhou, et al.","author":"Wei Jason","year":"2022","unstructured":"Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al., 2022. Chain-of-thought prompting elicits reasoning in large language models. 24824-24837 pages."},{"key":"e_1_3_2_1_24_1","unstructured":"Haotian Xu Xing Wu Weinong Wang Zhongzhi Li Da Zheng Boyuan Chen Yi Hu Shijia Kang Jiaming Ji Yingying Zhang et al. 2025. RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems? arXiv preprint arXiv:2501.11284 (2025)."},{"key":"e_1_3_2_1_25_1","unstructured":"Ziwei Xu Sanjay Jain and Mohan Kankanhalli. 2024. Hallucination is inevitable: An innate limitation of large language models."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"crossref","unstructured":"Zhilin Yang Peng Qi Saizheng Zhang Yoshua Bengio William W Cohen Ruslan Salakhutdinov and Christopher D Manning. 2018. HotpotQA: A dataset for diverse explainable multi-hop question answering.","DOI":"10.18653\/v1\/D18-1259"},{"key":"e_1_3_2_1_27_1","unstructured":"Wenhao Yu Dan Iter Shuohang Wang Yichong Xu Mingxuan Ju Soumya Sanyal Chenguang Zhu Michael Zeng and Meng Jiang. 2022. Generate rather than retrieve: Large language models are strong context generators."},{"key":"e_1_3_2_1_28_1","unstructured":"Weihao Zeng Yuzhen Huang Wei Liu Keqing He Qian Liu Zejun Ma and Junxian He. [n.d.]. 7b model and 8k examples: Emerging reasoning with reinforcement learning is both effective and efficient."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"crossref","unstructured":"Yunxiang Zhang Muhammad Khalifa Lajanugen Logeswaran Moontae Lee Honglak Lee and Lu Wang. 2023. Merging generated and retrieved knowledge for open-domain QA.","DOI":"10.18653\/v1\/2023.emnlp-main.286"}],"event":{"name":"CIKM '25: The 34th ACM International Conference on Information and Knowledge Management","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Seoul Republic of Korea","acronym":"CIKM '25"},"container-title":["Proceedings of the 34th ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3746252.3760903","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T02:09:23Z","timestamp":1765505363000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746252.3760903"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,10]]},"references-count":29,"alternative-id":["10.1145\/3746252.3760903","10.1145\/3746252"],"URL":"https:\/\/doi.org\/10.1145\/3746252.3760903","relation":{},"subject":[],"published":{"date-parts":[[2025,11,10]]},"assertion":[{"value":"2025-11-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}