{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T21:09:37Z","timestamp":1780607377768,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":67,"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\/3701551.3703573","type":"proceedings-article","created":{"date-parts":[[2025,2,26]],"date-time":"2025-02-26T12:30:16Z","timestamp":1740573016000},"page":"866-875","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9139-8004","authenticated-orcid":false,"given":"Zhankui","family":"He","sequence":"first","affiliation":[{"name":"University of California, San Diego, La Jolla, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6712-0063","authenticated-orcid":false,"given":"Zhouhang","family":"Xie","sequence":"additional","affiliation":[{"name":"University of California, San Diego, La Jolla, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-7448-8335","authenticated-orcid":false,"given":"Harald","family":"Steck","sequence":"additional","affiliation":[{"name":"Netflix Inc., Los Gatos, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9701-6473","authenticated-orcid":false,"given":"Dawen","family":"Liang","sequence":"additional","affiliation":[{"name":"Netflix Inc., Los Gatos, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0239-6972","authenticated-orcid":false,"given":"Rahul","family":"Jha","sequence":"additional","affiliation":[{"name":"Netflix Inc., Los Gatos, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1672-0507","authenticated-orcid":false,"given":"Nathan","family":"Kallus","sequence":"additional","affiliation":[{"name":"Netflix Inc., Los Gatos, California, USA, & Cornell University, New York, New York, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0955-7588","authenticated-orcid":false,"given":"Julian","family":"McAuley","sequence":"additional","affiliation":[{"name":"University of California, San Diego, La Jolla, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,3,10]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3610647"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608883"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-76298-0_52"},{"key":"e_1_3_2_1_4_1","volume-title":"Tallrec: An effective and efficient tuning framework to align large language model with recommendation. arXiv preprint arXiv:2305.00447","author":"Bao Keqin","year":"2023","unstructured":"Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, and Xiangnan He. 2023. Tallrec: An effective and efficient tuning framework to align large language model with recommendation. arXiv preprint arXiv:2305.00447 (2023)."},{"key":"e_1_3_2_1_5_1","unstructured":"Tom Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared D Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell et al. 2020b. Language models are few-shot learners. Advances in neural information processing systems Vol. 33 (2020) 1877--1901."},{"key":"e_1_3_2_1_6_1","volume-title":"Lin (Eds.)","volume":"33","author":"Brown Tom","year":"2020","unstructured":"Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020a. Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc., 1877--1901. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2020\/file\/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3564284"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11257-011-9108-6"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1189"},{"key":"e_1_3_2_1_10_1","volume-title":"Understanding Differential Search Index for Text Retrieval. arXiv preprint arXiv:2305.02073","author":"Chen Xiaoyang","year":"2023","unstructured":"Xiaoyang Chen, Yanjiang Liu, Ben He, Le Sun, and Yingfei Sun. 2023b. Understanding Differential Search Index for Text Retrieval. arXiv preprint arXiv:2305.02073 (2023)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/W14-4012"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9412102"},{"key":"e_1_3_2_1_13_1","unstructured":"Aakanksha Chowdhery Sharan Narang Jacob Devlin Maarten Bosma Gaurav Mishra Adam Roberts Paul Barham Hyung Won Chung Charles Sutton Sebastian Gehrmann Parker Schuh Kensen Shi Sasha Tsvyashchenko Joshua Maynez Abhishek Rao Parker Barnes Yi Tay Noam M. Shazeer Vinodkumar Prabhakaran Emily Reif Nan Du Benton C. Hutchinson Reiner Pope James Bradbury Jacob Austin Michael Isard Guy Gur-Ari Pengcheng Yin Toju Duke Anselm Levskaya Sanjay Ghemawat Sunipa Dev Henryk Michalewski Xavier Garc\u00eda Vedant Misra Kevin Robinson Liam Fedus Denny Zhou Daphne Ippolito David Luan Hyeontaek Lim Barret Zoph Alexander Spiridonov Ryan Sepassi David Dohan Shivani Agrawal Mark Omernick Andrew M. Dai Thanumalayan Sankaranarayana Pillai Marie Pellat Aitor Lewkowycz Erica Moreira Rewon Child Oleksandr Polozov Katherine Lee Zongwei Zhou Xuezhi Wang Brennan Saeta Mark D\u00edaz Orhan Firat Michele Catasta Jason Wei Kathleen S. Meier-Hellstern Douglas Eck Jeff Dean Slav Petrov and Noah Fiedel. 2022. PaLM: Scaling Language Modeling with Pathways. ArXiv Vol. abs\/2204.02311 (2022)."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939746"},{"key":"e_1_3_2_1_15_1","volume-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555","author":"Chung Junyoung","year":"2014","unstructured":"Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio. 2014. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555 (2014)."},{"key":"e_1_3_2_1_16_1","unstructured":"Zeyu Cui Jianxin Ma Chang Zhou Jingren Zhou and Hongxia Yang. 2022. M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems. arxiv: 2205.08084 [cs.IR]"},{"key":"e_1_3_2_1_17_1","volume-title":"Uncovering ChatGPT's Capabilities in Recommender Systems. arXiv preprint arXiv:2305.02182","author":"Dai Sunhao","year":"2023","unstructured":"Sunhao Dai, Ninglu Shao, Haiyuan Zhao, Weijie Yu, Zihua Si, Chen Xu, Zhongxiang Sun, Xiao Zhang, and Jun Xu. 2023. Uncovering ChatGPT's Capabilities in Recommender Systems. arXiv preprint arXiv:2305.02182 (2023)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11257-023-09364-z"},{"key":"e_1_3_2_1_19_1","volume-title":"A Large Language Model Enhanced Conversational Recommender System. arXiv preprint arXiv:2308.06212","author":"Feng Yue","year":"2023","unstructured":"Yue Feng, Shuchang Liu, Zhenghai Xue, Qingpeng Cai, Lantao Hu, Peng Jiang, Kun Gai, and Fei Sun. 2023. A Large Language Model Enhanced Conversational Recommender System. arXiv preprint arXiv:2308.06212 (2023)."},{"key":"e_1_3_2_1_20_1","unstructured":"Luke Friedman Sameer Ahuja David Allen Terry Tan Hakim Sidahmed Changbo Long Jun Xie Gabriel Schubiner Ajay Patel Harsh Lara et al. 2023. Leveraging Large Language Models in Conversational Recommender Systems. arXiv preprint arXiv:2305.07961 (2023)."},{"key":"e_1_3_2_1_21_1","volume-title":"Personalized Prompt & Predict Paradigm (P5). In RecSys '22: Sixteenth ACM Conference on Recommender Systems","author":"Geng Shijie","year":"2022","unstructured":"Shijie Geng, Shuchang Liu, Zuohui Fu, Yingqiang Ge, and Yongfeng Zhang. 2022. Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5). In RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18 - 23, 2022, Jennifer Golbeck, F. Maxwell Harper, Vanessa Murdock, Michael D. Ekstrand, Bracha Shapira, Justin Basilico, Keld T. Lundgaard, and Even Oldridge (Eds.). ACM, 299--315."},{"key":"e_1_3_2_1_22_1","volume-title":"International Conference on Machine Learning. PMLR, 3800--3809","author":"Gu Albert","year":"2020","unstructured":"Albert Gu, Caglar Gulcehre, Thomas Paine, Matt Hoffman, and Razvan Pascanu. 2020. Improving the gating mechanism of recurrent neural networks. In International Conference on Machine Learning. PMLR, 3800--3809."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3610639"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.654"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3614949"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3523227.3546755"},{"key":"e_1_3_2_1_27_1","volume-title":"Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531","author":"Hinton Geoffrey","year":"2015","unstructured":"Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015. Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 (2015)."},{"key":"e_1_3_2_1_28_1","volume-title":"Long short-term memory. Neural computation","author":"Hochreiter Sepp","year":"1997","unstructured":"Sepp Hochreiter and J\u00fcrgen Schmidhuber. 1997. Long short-term memory. Neural computation, Vol. 9, 8 (1997), 1735--1780."},{"key":"e_1_3_2_1_29_1","volume-title":"Large language models are zero-shot rankers for recommender systems. arXiv preprint arXiv:2305.08845","author":"Hou Yupeng","year":"2023","unstructured":"Yupeng Hou, Junjie Zhang, Zihan Lin, Hongyu Lu, Ruobing Xie, Julian McAuley, and Wayne Xin Zhao. 2023. Large language models are zero-shot rankers for recommender systems. arXiv preprint arXiv:2305.08845 (2023)."},{"key":"e_1_3_2_1_30_1","volume-title":"Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al.","author":"Jiang Albert Q","year":"2023","unstructured":"Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023. Mistral 7B. arXiv preprint arXiv:2310.06825 (2023)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487589"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00035"},{"key":"e_1_3_2_1_33_1","volume-title":"Chi, and Derek Zhiyuan Cheng","author":"Kang Wang-Cheng","year":"2023","unstructured":"Wang-Cheng Kang, Jianmo Ni, Nikhil Mehta, Maheswaran Sathiamoorthy, Lichan Hong, Ed Chi, and Derek Zhiyuan Cheng. 2023. Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. arXiv preprint arXiv:2305.06474 (2023)."},{"key":"e_1_3_2_1_34_1","volume-title":"Scaling Laws for Neural Language Models. ArXiv","author":"Kaplan Jared","year":"2020","unstructured":"Jared Kaplan, Sam McCandlish, T. J. Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeff Wu, and Dario Amodei. 2020. Scaling Laws for Neural Language Models. ArXiv, Vol. abs\/2001.08361 (2020)."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371769"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403258"},{"key":"e_1_3_2_1_37_1","unstructured":"Jinming Li Wentao Zhang Tian Wang Guanglei Xiong Alan Lu and Gerard Medioni. 2023. GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation. arxiv: 2304.03879 [cs.IR]"},{"key":"e_1_3_2_1_38_1","volume-title":"Hannes Schulz, Vincent Michalski, Laurent Charlin, and Chris Pal.","author":"Li Raymond","year":"2018","unstructured":"Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, and Chris Pal. 2018. Towards deep conversational recommendations. Advances in neural information processing systems, Vol. 31 (2018)."},{"key":"e_1_3_2_1_39_1","volume-title":"Bodhisattwa Prasad Majumder, and Julian McAuley","author":"Li Shuyang","year":"2021","unstructured":"Shuyang Li, Bodhisattwa Prasad Majumder, and Julian McAuley. 2021. Self-Supervised Bot Play for Conversational Recommendation with Justifications. arXiv preprint arXiv:2112.05197 (2021)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3532074"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.abq1158"},{"key":"e_1_3_2_1_42_1","volume-title":"ConceptNet-a practical commonsense reasoning tool-kit. BT technology journal","author":"Liu Hugo","year":"2004","unstructured":"Hugo Liu and Push Singh. 2004. ConceptNet-a practical commonsense reasoning tool-kit. BT technology journal, Vol. 22, 4 (2004), 211--226."},{"key":"e_1_3_2_1_43_1","unstructured":"Junling Liu Chao Liu Renjie Lv Kang Zhou and Yan Zhang. 2023. Is ChatGPT a Good Recommender? A Preliminary Study. arxiv: 2304.10149 [cs.IR]"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.99"},{"key":"e_1_3_2_1_45_1","volume-title":"Large Language Model Augmented Narrative Driven Recommendations. arXiv preprint arXiv:2306.02250","author":"Mysore Sheshera","year":"2023","unstructured":"Sheshera Mysore, Andrew McCallum, and Hamed Zamani. 2023. Large Language Model Augmented Narrative Driven Recommendations. arXiv preprint arXiv:2306.02250 (2023)."},{"key":"e_1_3_2_1_46_1","volume-title":"Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748","author":"van den Oord Aaron","year":"2018","unstructured":"Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748 (2018)."},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1410"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608845"},{"key":"e_1_3_2_1_49_1","volume-title":"Liam Fedus, Luke Metz, Michael Pokorny, Rapha Gontijo Lopes, and Sengjia Zhao.","author":"Schulman John","year":"2022","unstructured":"John Schulman, Barret Zoph, C Kim, Jacob Hilton, Jacob Menick, Jiayi Weng, Juan Felipe Ceron Uribe, Liam Fedus, Luke Metz, Michael Pokorny, Rapha Gontijo Lopes, and Sengjia Zhao. 2022. Chatgpt: Optimizing language models for dialogue. OpenAI (2022)."},{"key":"e_1_3_2_1_50_1","volume-title":"One embedder, any task: Instruction-finetuned text embeddings. arXiv preprint arXiv:2212.09741","author":"Su Hongjin","year":"2022","unstructured":"Hongjin Su, Weijia Shi, Jungo Kasai, Yizhong Wang, Yushi Hu, Mari Ostendorf, Wen-tau Yih, Noah A Smith, Luke Zettlemoyer, and Tao Yu. 2022. One embedder, any task: Instruction-finetuned text embeddings. arXiv preprint arXiv:2212.09741 (2022)."},{"key":"e_1_3_2_1_51_1","first-page":"21831","article-title":"Transformer memory as a differentiable search index","volume":"35","author":"Tay Yi","year":"2022","unstructured":"Yi Tay, Vinh Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Gupta, et al. 2022. Transformer memory as a differentiable search index. Advances in Neural Information Processing Systems, Vol. 35 (2022), 21831--21843.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_52_1","unstructured":"MosaicML NLP Team. 2023. Introducing MPT-7B: A New Standard for Open-Source Commercially Usable LLMs. www.mosaicml.com\/blog\/mpt-7b Accessed: 2023-05-05."},{"key":"e_1_3_2_1_53_1","unstructured":"Hugo Touvron Louis Martin Kevin Stone Peter Albert Amjad Almahairi Yasmine Babaei Nikolay Bashlykov Soumya Batra Prajjwal Bhargava Shruti Bhosale et al. 2023. Llama 2: Open foundation and fine-tuned chat models. arXiv preprint arXiv:2307.09288 (2023)."},{"key":"e_1_3_2_1_54_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998--6008."},{"key":"e_1_3_2_1_55_1","volume-title":"Generative Recommendation: Towards Next-generation Recommender Paradigm. arxiv: 2304.03516 [cs.IR]","author":"Wang Wenjie","year":"2023","unstructured":"Wenjie Wang, Xinyu Lin, Fuli Feng, Xiangnan He, and Tat-Seng Chua. 2023a. Generative Recommendation: Towards Next-generation Recommender Paradigm. arxiv: 2304.03516 [cs.IR]"},{"key":"e_1_3_2_1_56_1","volume-title":"Jingyuan Wang, and Ji-Rong Wen.","author":"Wang Xiaolei","year":"2023","unstructured":"Xiaolei Wang, Xinyu Tang, Wayne Xin Zhao, Jingyuan Wang, and Ji-Rong Wen. 2023c. Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models. arXiv preprint arXiv:2305.13112 (2023)."},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539382"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/3547333"},{"key":"e_1_3_2_1_59_1","volume-title":"Oh (Eds.)","volume":"35","author":"Wei Jason","year":"2022","unstructured":"Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed Chi, Quoc V Le, and Denny Zhou. 2022. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. In Advances in Neural Information Processing Systems, S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, and A. Oh (Eds.), Vol. 35. Curran Associates, Inc., 24824--24837. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2022\/file\/9d5609613524ecf4f15af0f7b31abca4-Paper-Conference.pdf"},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347009"},{"key":"e_1_3_2_1_61_1","volume-title":"Dong Wang, and Even Oldridge.","author":"Yue Zhenrui","year":"2023","unstructured":"Zhenrui Yue, Sara Rabhi, Gabriel de Souza Pereira Moreira, Dong Wang, and Even Oldridge. 2023. LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking. arXiv preprint arXiv:2311.02089 (2023)."},{"key":"e_1_3_2_1_62_1","volume-title":"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. 270--278","author":"Zhang Yizhe","year":"2020","unstructured":"Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, and William B Dolan. 2020. DIALOGPT: Large-Scale Generative Pre-training for Conversational Response Generation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. 270--278."},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512088"},{"key":"e_1_3_2_1_64_1","volume-title":"International Conference on Machine Learning. PMLR, 12697--12706","author":"Zhao Zihao","year":"2021","unstructured":"Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh. 2021. Calibrate before use: Improving few-shot performance of language models. In International Conference on Machine Learning. PMLR, 12697--12706."},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"crossref","unstructured":"Qinkai Zheng Xiao Xia Xu Zou Yuxiao Dong Shan Wang Yufei Xue Zihan Wang Lei Shen Andi Wang Yang Li Teng Su Zhilin Yang and Jie Tang. 2023. CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Evaluations on HumanEval-X. arxiv: 2303.17568 [cs.LG]","DOI":"10.1145\/3580305.3599790"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403143"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531852"}],"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\/3701551.3703573","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3701551.3703573","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T09:12:40Z","timestamp":1755767560000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3701551.3703573"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,10]]},"references-count":67,"alternative-id":["10.1145\/3701551.3703573","10.1145\/3701551"],"URL":"https:\/\/doi.org\/10.1145\/3701551.3703573","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"}}]}}