{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T00:46:25Z","timestamp":1774399585337,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":57,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T00:00:00Z","timestamp":1741564800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,3,10]]},"DOI":"10.1145\/3701551.3703583","type":"proceedings-article","created":{"date-parts":[[2025,2,26]],"date-time":"2025-02-26T12:33:36Z","timestamp":1740573216000},"page":"944-953","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["MCRanker: Generating Diverse Criteria On-the-Fly to Improve Pointwise LLM Rankers"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-2903-5087","authenticated-orcid":false,"given":"Fang","family":"Guo","sequence":"first","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2792-4303","authenticated-orcid":false,"given":"Wenyu","family":"Li","sequence":"additional","affiliation":[{"name":"South China University of Technology, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8134-1509","authenticated-orcid":false,"given":"Honglei","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Google, Seattle, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0448-9224","authenticated-orcid":false,"given":"Yun","family":"Luo","sequence":"additional","affiliation":[{"name":"Westlake University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7895-9997","authenticated-orcid":false,"given":"Yafu","family":"Li","sequence":"additional","affiliation":[{"name":"Westlake University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1323-0545","authenticated-orcid":false,"given":"Le","family":"Yan","sequence":"additional","affiliation":[{"name":"Google, Mountain View, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0129-8542","authenticated-orcid":false,"given":"Qi","family":"Zhu","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hanghzou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5214-2268","authenticated-orcid":false,"given":"Yue","family":"Zhang","sequence":"additional","affiliation":[{"name":"Westlake University, Hangzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2025,3,10]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Proceedings of The Second Arabic Natural Language Processing Conference. 11--26","author":"Mutairi Mariam","year":"2024","unstructured":"Mariam ALMutairi, Lulwah AlKulaib, Melike Aktas, Sara Alsalamah, and Chang- Tien Lu. 2024. Synthetic Arabic Medical Dialogues Using Advanced Multi-Agent LLM Techniques. In Proceedings of The Second Arabic Natural Language Processing Conference. 11--26."},{"key":"e_1_3_2_1_2_1","volume-title":"ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs. arXiv:2309","author":"Chih-Yao Chen Justin","year":"2024","unstructured":"Justin Chih-Yao Chen, Swarnadeep Saha, and Mohit Bansal. 2024. ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs. arXiv:2309.13007 [cs.CL]"},{"key":"e_1_3_2_1_3_1","volume-title":"Toxicity in chatgpt: Analyzing persona-assigned language models. arXiv preprint arXiv:2304.05335","author":"Deshpande Ameet","year":"2023","unstructured":"Ameet Deshpande, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, and Karthik Narasimhan. 2023. Toxicity in chatgpt: Analyzing persona-assigned language models. arXiv preprint arXiv:2304.05335 (2023)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Guglielmo Faggioli Laura Dietz Charles Clarke Gianluca Demartini Matthias Hagen Claudia Hauff Noriko Kando Evangelos Kanoulas Martin Potthast Benno Stein et al. 2024. Who Determines What Is Relevant? Humans or AI? Why Not Both? A spectrum of human-AI collaboration in assessing relevance. Commun. ACM (2024).","DOI":"10.1145\/3624730"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3578337.3605136"},{"key":"e_1_3_2_1_6_1","unstructured":"Jinlan Fu See-Kiong Ng Zhengbao Jiang and Pengfei Liu. 2023. GPTScore: Evaluate as You Desire. arXiv:2302.04166 [cs.CL] https:\/\/arxiv.org\/abs\/2302.04166"},{"key":"e_1_3_2_1_7_1","volume-title":"Improving language model negotiation with self-play and in-context learning from ai feedback. arXiv preprint arXiv:2305.10142","author":"Fu Yao","year":"2023","unstructured":"Yao Fu, Hao Peng, Tushar Khot, and Mirella Lapata. 2023. Improving language model negotiation with self-play and in-context learning from ai feedback. arXiv preprint arXiv:2305.10142 (2023)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1.13715"},{"key":"e_1_3_2_1_9_1","volume-title":"Learning-to-Rank with BERT in TF-Ranking. arXiv preprint arXiv:2004.08476","author":"Han Shuguang","year":"2020","unstructured":"Shuguang Han, Xuanhui Wang, Mike Bendersky, and Marc Najork. 2020. Learning-to-Rank with BERT in TF-Ranking. arXiv preprint arXiv:2004.08476 (2020)."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/582415.582418"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3613904.3642216"},{"key":"e_1_3_2_1_12_1","volume-title":"Stance detection with collaborative role-infused llm-based agents. arXiv preprint arXiv:2310.10467","author":"Lan Xiaochong","year":"2023","unstructured":"Xiaochong Lan, Chen Gao, Depeng Jin, and Yong Li. 2023. Stance detection with collaborative role-infused llm-based agents. arXiv preprint arXiv:2310.10467 (2023)."},{"key":"e_1_3_2_1_13_1","first-page":"1","article-title":"PARADE: Passage Representation Aggregation forDocument Reranking","volume":"42","author":"Li Canjia","year":"2023","unstructured":"Canjia Li, Andrew Yates, Sean MacAvaney, Ben He, and Yingfei Sun. 2023. PARADE: Passage Representation Aggregation forDocument Reranking. ACM Transactions on Information Systems 42, 2 (2023), 1--26.","journal-title":"ACM Transactions on Information Systems"},{"key":"e_1_3_2_1_14_1","volume-title":"Hani Itani, Dmitrii Khizbullin, and Bernard Ghanem.","author":"Li Guohao","year":"2023","unstructured":"Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, Dmitrii Khizbullin, and Bernard Ghanem. 2023. Camel: Communicative agents for ''mind'' exploration of large scale language model society. arXiv preprint arXiv:2303.17760 (2023)."},{"key":"e_1_3_2_1_15_1","unstructured":"Margaret Li Suchin Gururangan Tim Dettmers Mike Lewis Tim Althoff Noah A. Smith and Luke Zettlemoyer. 2022. Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models. arXiv:2208.03306 [cs.CL]"},{"key":"e_1_3_2_1_16_1","unstructured":"Zhen Li Xiaohan Xu Tao Shen Can Xu Jia-Chen Gu Yuxuan Lai Chongyang Tao and Shuai Ma. 2024. Leveraging Large Language Models for NLG Evaluation: Advances and Challenges. arXiv:2401.07103 [cs.CL] https:\/\/arxiv.org\/abs\/2401. 07103"},{"key":"e_1_3_2_1_17_1","unstructured":"Percy Liang Rishi Bommasani Tony Lee Dimitris Tsipras Dilara Soylu Michihiro Yasunaga Yian Zhang Deepak Narayanan YuhuaiWu Ananya Kumar et al. 2022. Holistic evaluation of language models. arXiv preprint arXiv:2211.09110 (2022)."},{"key":"e_1_3_2_1_18_1","volume-title":"Encouraging divergent thinking in large language models through multi-agent debate. arXiv preprint arXiv:2305.19118","author":"Liang Tian","year":"2023","unstructured":"Tian Liang, Zhiwei He, Wenxiang Jiao, Xing Wang, Yan Wang, Rui Wang, Yujiu Yang, Zhaopeng Tu, and Shuming Shi. 2023. Encouraging divergent thinking in large language models through multi-agent debate. arXiv preprint arXiv:2305.19118 (2023)."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Tie-Yan Liu et al. 2009. Learning to rank for information retrieval. Foundations and Trends\u00ae in Information Retrieval 3 3 (2009) 225--331.","DOI":"10.1561\/1500000016"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Yang Liu Dan Iter Yichong Xu Shuohang Wang Ruochen Xu and Chenguang Zhu. 2023. G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment. arXiv:2303.16634 [cs.CL] https:\/\/arxiv.org\/abs\/2303.16634","DOI":"10.18653\/v1\/2023.emnlp-main.153"},{"key":"e_1_3_2_1_21_1","unstructured":"Yuxuan Liu Tianchi Yang Shaohan Huang Zihan Zhang Haizhen Huang Furu Wei Weiwei Deng Feng Sun and Qi Zhang. 2023. Calibrating LLM-Based Evaluator. arXiv:2309.13308 [cs.CL] https:\/\/arxiv.org\/abs\/2309.13308"},{"key":"e_1_3_2_1_22_1","volume-title":"Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2421--2425","author":"Ma Xueguang","year":"2024","unstructured":"Xueguang Ma, Liang Wang, Nan Yang, Furu Wei, and Jimmy Lin. 2024. Finetuning llama for multi-stage text retrieval. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2421--2425."},{"key":"e_1_3_2_1_23_1","volume-title":"Zeroshot listwise document reranking with a large language model. arXiv preprint arXiv:2305.02156","author":"Ma Xueguang","year":"2023","unstructured":"Xueguang Ma, Xinyu Zhang, Ronak Pradeep, and Jimmy Lin. 2023. Zeroshot listwise document reranking with a large language model. arXiv preprint arXiv:2305.02156 (2023)."},{"key":"e_1_3_2_1_24_1","unstructured":"Liam Magee Vanicka Arora Gus Gollings and Norma Lam-Saw. 2024. The Drama Machine: Simulating Character Development with LLM Agents. arXiv:2408.01725 [cs.CY] https:\/\/arxiv.org\/abs\/2408.01725"},{"key":"e_1_3_2_1_25_1","volume-title":"DERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agents. arXiv:2303.17071 [cs.CL]","author":"Nair Varun","year":"2023","unstructured":"Varun Nair, Elliot Schumacher, Geoffrey Tso, and Anitha Kannan. 2023. DERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agents. arXiv:2303.17071 [cs.CL]"},{"key":"e_1_3_2_1_26_1","volume-title":"Document ranking with a pretrained sequence-to-sequence model. arXiv preprint arXiv:2003.06713","author":"Nogueira Rodrigo","year":"2020","unstructured":"Rodrigo Nogueira, Zhiying Jiang, and Jimmy Lin. 2020. Document ranking with a pretrained sequence-to-sequence model. arXiv preprint arXiv:2003.06713 (2020)."},{"key":"e_1_3_2_1_27_1","volume-title":"Multi-stage document ranking with BERT. arXiv preprint arXiv:1910.14424","author":"Nogueira Rodrigo","year":"2019","unstructured":"Rodrigo Nogueira, Wei Yang, Kyunghyun Cho, and Jimmy Lin. 2019. Multi-stage document ranking with BERT. arXiv preprint arXiv:1910.14424 (2019)."},{"key":"e_1_3_2_1_28_1","volume-title":"Rankvicuna: Zero-shot listwise document reranking with open-source large language models. arXiv preprint arXiv:2309.15088","author":"Pradeep Ronak","year":"2023","unstructured":"Ronak Pradeep, Sahel Sharifymoghaddam, and Jimmy Lin. 2023. Rankvicuna: Zero-shot listwise document reranking with open-source large language models. arXiv preprint arXiv:2309.15088 (2023)."},{"key":"e_1_3_2_1_29_1","volume-title":"RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze! arXiv preprint arXiv:2312.02724","author":"Pradeep Ronak","year":"2023","unstructured":"Ronak Pradeep, Sahel Sharifymoghaddam, and Jimmy Lin. 2023. RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze! arXiv preprint arXiv:2312.02724 (2023)."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-naacl.97"},{"key":"e_1_3_2_1_31_1","volume-title":"International Conference on Learning Representations.","author":"Qin Zhen","year":"2020","unstructured":"Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, and Marc Najork. 2020. Are neural rankers still outperformed by gradient boosted decision trees?. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"crossref","unstructured":"Vyas Raina Adian Liusie and Mark Gales. 2024. Is LLM-as-a-Judge Robust? Investigating Universal Adversarial Attacks on Zero-shot LLM Assessment. arXiv:2402.14016 [cs.CL]","DOI":"10.18653\/v1\/2024.emnlp-main.427"},{"key":"e_1_3_2_1_33_1","volume-title":"Improving passage retrieval with zero-shot question generation. arXiv preprint arXiv:2204.07496","author":"Sachan Devendra Singh","year":"2022","unstructured":"Devendra Singh Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan,Wen-tau Yih, Joelle Pineau, and Luke Zettlemoyer. 2022. Improving passage retrieval with zero-shot question generation. arXiv preprint arXiv:2204.07496 (2022)."},{"key":"e_1_3_2_1_34_1","volume-title":"Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models. arXiv preprint arXiv:2402.14207","author":"Shao Yijia","year":"2024","unstructured":"Yijia Shao, Yucheng Jiang, Theodore A Kanell, Peter Xu, Omar Khattab, and Monica S Lam. 2024. Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models. arXiv preprint arXiv:2402.14207 (2024)."},{"key":"e_1_3_2_1_35_1","volume-title":"From Data to Story: Towards Automatic Animated Data Video Creation with LLM-based Multi-Agent Systems. arXiv preprint arXiv:2408.03876","author":"Shen Leixian","year":"2024","unstructured":"Leixian Shen, Haotian Li, Yun Wang, and Huamin Qu. 2024. From Data to Story: Towards Automatic Animated Data Video Creation with LLM-based Multi-Agent Systems. arXiv preprint arXiv:2408.03876 (2024)."},{"key":"e_1_3_2_1_36_1","volume-title":"Agentic LLM Workflows for Generating Patient-Friendly Medical Reports. arXiv preprint arXiv:2408.01112","author":"Sudarshan Malavikha","year":"2024","unstructured":"Malavikha Sudarshan, Sophie Shih, Estella Yee, Alina Yang, John Zou, Cathy Chen, Quan Zhou, Leon Chen, Chinmay Singhal, and George Shih. 2024. Agentic LLM Workflows for Generating Patient-Friendly Medical Reports. arXiv preprint arXiv:2408.01112 (2024)."},{"key":"e_1_3_2_1_37_1","volume-title":"Is chatgpt good at search? investigating large language models as re-ranking agent. arXiv preprint arXiv:2304.09542","author":"Sun Weiwei","year":"2023","unstructured":"Weiwei Sun, Lingyong Yan, Xinyu Ma, Pengjie Ren, Dawei Yin, and Zhaochun Ren. 2023. Is chatgpt good at search? investigating large language models as re-ranking agent. arXiv preprint arXiv:2304.09542 (2023)."},{"key":"e_1_3_2_1_38_1","volume-title":"BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models. arXiv:2104.08663 [cs.IR] https:\/\/arxiv.org\/abs\/ 2104.08663","author":"Thakur Nandan","year":"2021","unstructured":"Nandan Thakur, Nils Reimers, Andreas R\u00fcckl\u00e9, Abhishek Srivastava, and Iryna Gurevych. 2021. BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models. arXiv:2104.08663 [cs.IR] https:\/\/arxiv.org\/abs\/ 2104.08663"},{"key":"e_1_3_2_1_39_1","volume-title":"Large language models can accurately predict searcher preferences. arXiv preprint arXiv:2309.10621","author":"Thomas Paul","year":"2023","unstructured":"Paul Thomas, Seth Spielman, Nick Craswell, and Bhaskar Mitra. 2023. Large language models can accurately predict searcher preferences. arXiv preprint arXiv:2309.10621 (2023)."},{"key":"e_1_3_2_1_40_1","volume-title":"Best Practices for Managing Data Annotation Projects. CoRR abs\/2009.11654","author":"Tseng Tina","year":"2020","unstructured":"Tina Tseng, Amanda Stent, and Domenic Maida. 2020. Best Practices for Managing Data Annotation Projects. CoRR abs\/2009.11654 (2020). arXiv:2009.11654 https:\/\/arxiv.org\/abs\/2009.11654"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W19-8643"},{"key":"e_1_3_2_1_42_1","volume-title":"DORIS-MAE: Scientific document retrieval using multi-level aspect-based queries. arXiv preprint arXiv:2310.04678","author":"Wang Jianyou","year":"2023","unstructured":"Jianyou Wang, Kaicheng Wang, Xiaoyue Wang, Prudhviraj Naidu, Leon Bergen, and Ramamohan Paturi. 2023. DORIS-MAE: Scientific document retrieval using multi-level aspect-based queries. arXiv preprint arXiv:2310.04678 (2023)."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.901"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"crossref","unstructured":"Qineng Wang Zihao Wang Ying Su Hanghang Tong and Yangqiu Song. 2024. Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key? arXiv:2402.18272 [cs.CL]","DOI":"10.18653\/v1\/2024.acl-long.331"},{"key":"e_1_3_2_1_45_1","volume-title":"Unleashing the emergent cognitive synergy in large language models: A task-solving agent through multi-persona self-collaboration. arXiv preprint arXiv:2307.05300","author":"Wang Zhenhailong","year":"2023","unstructured":"Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, Tao Ge, Furu Wei, and Heng Ji. 2023. Unleashing the emergent cognitive synergy in large language models: A task-solving agent through multi-persona self-collaboration. arXiv preprint arXiv:2307.05300 (2023)."},{"key":"e_1_3_2_1_46_1","unstructured":"Qingyun Wu Gagan Bansal Jieyu Zhang Yiran Wu Beibin Li Erkang Zhu Li Jiang Xiaoyun Zhang Shaokun Zhang Jiale Liu et al. [n.d.]. AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversations. ([n. d.])."},{"key":"e_1_3_2_1_47_1","volume-title":"Learning List-Level Domain-Invariant Representations for Ranking. Advances in Neural Information Processing Systems 36","author":"Xian Ruicheng","year":"2023","unstructured":"Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, XuanhuiWang, and Michael Bendersky. 2023. Learning List-Level Domain-Invariant Representations for Ranking. Advances in Neural Information Processing Systems 36 (2023)."},{"key":"e_1_3_2_1_48_1","volume-title":"Expertprompting: Instructing large language models to be distinguished experts. arXiv preprint arXiv:2305.14688","author":"Xu Benfeng","year":"2023","unstructured":"Benfeng Xu, An Yang, Junyang Lin, Quan Wang, Chang Zhou, Yongdong Zhang, and Zhendong Mao. 2023. Expertprompting: Instructing large language models to be distinguished experts. arXiv preprint arXiv:2305.14688 (2023)."},{"key":"e_1_3_2_1_49_1","volume-title":"Exploring collaboration mechanisms for llm agents: A social psychology view. arXiv preprint arXiv:2310.02124","author":"Zhang Jintian","year":"2023","unstructured":"Jintian Zhang, Xin Xu, and Shumin Deng. 2023. Exploring collaboration mechanisms for llm agents: A social psychology view. arXiv preprint arXiv:2310.02124 (2023)."},{"key":"e_1_3_2_1_50_1","volume-title":"Rank-without-gpt: Building gpt-independent listwise rerankers on open-source large language models. arXiv preprint arXiv:2312.02969","author":"Zhang Xinyu","year":"2023","unstructured":"Xinyu Zhang, Sebastian Hofst\u00e4tter, Patrick Lewis, Raphael Tang, and Jimmy Lin. 2023. Rank-without-gpt: Building gpt-independent listwise rerankers on open-source large language models. arXiv preprint arXiv:2312.02969 (2023)."},{"key":"e_1_3_2_1_51_1","volume-title":"LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration. arXiv preprint arXiv:2402.11550","author":"Zhao Jun","year":"2024","unstructured":"Jun Zhao, Can Zu, Hao Xu, Yi Lu, Wei He, Yiwen Ding, Tao Gui, Qi Zhang, and Xuanjing Huang. 2024. LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration. arXiv preprint arXiv:2402.11550 (2024)."},{"key":"e_1_3_2_1_52_1","volume-title":"ReDel: A Toolkit for LLM-Powered Recursive Multi-Agent Systems. arXiv preprint arXiv:2408.02248","author":"Zhu Andrew","year":"2024","unstructured":"Andrew Zhu, Liam Dugan, and Chris Callison-Burch. 2024. ReDel: A Toolkit for LLM-Powered Recursive Multi-Agent Systems. arXiv preprint arXiv:2408.02248 (2024)."},{"key":"e_1_3_2_1_53_1","unstructured":"Yutao Zhu Huaying Yuan Shuting Wang Jiongnan Liu Wenhan Liu Chenlong Deng Haonan Chen Zhicheng Dou and Ji-Rong Wen. 2024. Large Language Models for Information Retrieval: A Survey. arXiv:2308.07107 [cs.CL] https: \/\/arxiv.org\/abs\/2308.07107"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3471158.3472238"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.naacl-short.31"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3592047"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626772.3657813"}],"event":{"name":"WSDM '25: The Eighteenth ACM International Conference on Web Search and Data Mining","location":"Hannover Germany","acronym":"WSDM '25","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3701551.3703583","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3701551.3703583","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T09:16:55Z","timestamp":1755767815000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3701551.3703583"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,10]]},"references-count":57,"alternative-id":["10.1145\/3701551.3703583","10.1145\/3701551"],"URL":"https:\/\/doi.org\/10.1145\/3701551.3703583","relation":{},"subject":[],"published":{"date-parts":[[2025,3,10]]},"assertion":[{"value":"2025-03-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}