{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T00:48:26Z","timestamp":1774399706433,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":85,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T00:00:00Z","timestamp":1720569600000},"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":[[2024,7,10]]},"DOI":"10.1145\/3626772.3657746","type":"proceedings-article","created":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T12:40:05Z","timestamp":1720701605000},"page":"469-480","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Planning Ahead in Generative Retrieval: Guiding Autoregressive Generation through Simultaneous Decoding"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2699-8460","authenticated-orcid":false,"given":"Hansi","family":"Zeng","sequence":"first","affiliation":[{"name":"University of Massachusetts Amherst, Amherst, MA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5339-5817","authenticated-orcid":false,"given":"Chen","family":"Luo","sequence":"additional","affiliation":[{"name":"Amazon, Palo Alto, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0800-3340","authenticated-orcid":false,"given":"Hamed","family":"Zamani","sequence":"additional","affiliation":[{"name":"University of Massachusetts Amherst, Amherst, MA, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,7,11]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2361319"},{"key":"e_1_3_2_1_2_1","volume-title":"Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors. ArXiv","author":"Baranchuk Dmitry","unstructured":"Dmitry Baranchuk, Artem Babenko, and Yury Malkov. 2018. Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors. ArXiv, Vol. abs\/1802.02422. https:\/\/api.semanticscholar.org\/CorpusID:3602418"},{"key":"e_1_3_2_1_3_1","volume-title":"Sebastian Riedel, and Fabio Petroni.","author":"Bevilacqua Michele","year":"2022","unstructured":"Michele Bevilacqua, Giuseppe Ottaviano, Patrick Lewis, Wen tau Yih, Sebastian Riedel, and Fabio Petroni. 2022. Autoregressive Search Engines: Generating Substrings as Document Identifiers. ArXiv, Vol. abs\/2204.10628. https:\/\/api.semanticscholar.org\/CorpusID:248366293"},{"key":"e_1_3_2_1_4_1","volume-title":"MS MARCO: A Human Generated MAchine Reading COmprehension Dataset. ArXiv","author":"Campos Daniel Fernando","year":"2016","unstructured":"Daniel Fernando Campos, Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, Li Deng, and Bhaskar Mitra. 2016. MS MARCO: A Human Generated MAchine Reading COmprehension Dataset. ArXiv, Vol. abs\/1611.09268. https:\/\/api.semanticscholar.org\/CorpusID:1289517"},{"key":"e_1_3_2_1_5_1","volume-title":"Autoregressive Entity Retrieval. ArXiv","author":"Cao Nicola De","unstructured":"Nicola De Cao, Gautier Izacard, Sebastian Riedel, and Fabio Petroni. 2020. Autoregressive Entity Retrieval. ArXiv, Vol. abs\/2010.00904. https:\/\/api.semanticscholar.org\/CorpusID:222125277"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3614821"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591631"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531827"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557271"},{"key":"e_1_3_2_1_10_1","volume-title":"Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One? ArXiv","author":"Chen Xilun","unstructured":"Xilun Chen, Kushal Lakhotia, Barlas O?uz, Anchit Gupta, Patrick Lewis, Stanislav Peshterliev, Yashar Mehdad, Sonal Gupta, and Wen tau Yih. 2021. Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One? ArXiv, Vol. abs\/2110.06918. https:\/\/api.semanticscholar.org\/CorpusID:238744204"},{"key":"e_1_3_2_1_11_1","volume-title":"Switzerland)","author":"Chen Yongjian","unstructured":"Yongjian Chen, Tao Guan, and Cheng Wang. 2010. Approximate Nearest Neighbor Search by Residual Vector Quantization. Sensors (Basel, Switzerland), Vol. 10, 11259--11273. https:\/\/api.semanticscholar.org\/CorpusID:33774240"},{"key":"e_1_3_2_1_12_1","unstructured":"David R. Cheriton. 2019. From doc2query to docTTTTTquery. https:\/\/api.semanticscholar.org\/CorpusID:208612557"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557456"},{"key":"e_1_3_2_1_14_1","unstructured":"Hyung Won Chung et al. 2022. Scaling Instruction-Finetuned Language Models. ArXiv Vol. abs\/2210.11416. https:\/\/api.semanticscholar.org\/CorpusID:253018554"},{"key":"e_1_3_2_1_15_1","volume-title":"Overview of the TREC 2019 Deep Learning Track. In TREC.","author":"Craswell Nick","year":"2019","unstructured":"Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos. 2019. Overview of the TREC 2019 Deep Learning Track. In TREC."},{"key":"e_1_3_2_1_16_1","volume-title":"Overview of the TREC 2020 Deep Learning Track. ArXiv","volume":"2102","author":"Craswell Nick","unstructured":"Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Fernando Campos, and Ellen M. Voorhees. 2021. Overview of the TREC 2020 Deep Learning Track. ArXiv, Vol. abs\/2102.07662. https:\/\/api.semanticscholar.org\/CorpusID:212737158"},{"key":"e_1_3_2_1_17_1","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In North American","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In North American Chapter of the Association for Computational Linguistics. https:\/\/api.semanticscholar.org\/CorpusID:52967399"},{"key":"e_1_3_2_1_18_1","volume-title":"SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval. ArXiv","author":"Formal Thibault","unstructured":"Thibault Formal, C. Lassance, Benjamin Piwowarski, and St\u00e9phane Clinchant. 2021a. SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval. ArXiv, Vol. abs\/2109.10086. https:\/\/api.semanticscholar.org\/CorpusID:237581550"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3463098"},{"key":"e_1_3_2_1_20_1","volume-title":"Sequence Transduction with Recurrent Neural Networks. ArXiv","author":"Graves Alex","year":"1941","unstructured":"Alex Graves. 2012. Sequence Transduction with Recurrent Neural Networks. ArXiv, Vol. abs\/1211.3711. https:\/\/api.semanticscholar.org\/CorpusID:17194112"},{"key":"e_1_3_2_1_21_1","volume-title":"International conference on machine learning. PMLR, 3929--3938","author":"Guu Kelvin","year":"2020","unstructured":"Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Mingwei Chang. 2020. Retrieval augmented language model pre-training. In International conference on machine learning. PMLR, 3929--3938."},{"key":"e_1_3_2_1_22_1","volume-title":"Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation. ArXiv","author":"Hofst\u00e4tter Sebastian","unstructured":"Sebastian Hofst\u00e4tter, Sophia Althammer, Michael Schr\u00f6der, Mete Sertkan, and Allan Hanbury. 2020. Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation. ArXiv, Vol. abs\/2010.02666. https:\/\/api.semanticscholar.org\/CorpusID:222141041"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591687"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462891"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591769"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2011.5946540"},{"key":"e_1_3_2_1_27_1","unstructured":"Bowen Jin Hansi Zeng Guoyin Wang Xiusi Chen Tianxin Wei Ruirui Li Zhengyang Wang Zheng Li Yang Li Hanqing Lu et al. 2023. Language Models As Semantic Indexers. arXiv preprint arXiv:2310.07815."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2019.2921572"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2019.2921572"},{"key":"e_1_3_2_1_30_1","volume-title":"Dense Passage Retrieval for Open-Domain Question Answering. In Conference on Empirical Methods in Natural Language Processing. https:\/\/api.semanticscholar.org\/CorpusID:215737187","author":"Karpukhin Vladimir","year":"2020","unstructured":"Vladimir Karpukhin, Barlas O?uz, Sewon Min, Patrick Lewis, Ledell Yu Wu, Sergey Edunov, Danqi Chen, and Wen tau Yih. 2020. Dense Passage Retrieval for Open-Domain Question Answering. In Conference on Empirical Methods in Natural Language Processing. https:\/\/api.semanticscholar.org\/CorpusID:215737187"},{"key":"e_1_3_2_1_31_1","volume-title":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:216553223","author":"Khattab O.","unstructured":"O. Khattab and Matei A. Zaharia. 2020a. ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:216553223"},{"key":"e_1_3_2_1_32_1","volume-title":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:216553223","author":"Khattab O.","unstructured":"O. Khattab and Matei A. Zaharia. 2020b. ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:216553223"},{"key":"e_1_3_2_1_33_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2014","unstructured":"Diederik P. Kingma and Jimmy Ba. 2014. Adam: A Method for Stochastic Optimization. CoRR, Vol. abs\/1412.6980. https:\/\/api.semanticscholar.org\/CorpusID:6628106"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00276"},{"key":"e_1_3_2_1_35_1","volume-title":"Nonparametric Decoding for Generative Retrieval. In Annual Meeting of the Association for Computational Linguistics. https:\/\/api.semanticscholar.org\/CorpusID:258959550","author":"Lee Hyunji","year":"2022","unstructured":"Hyunji Lee, Jaeyoung Kim, Hoyeon Chang, Hanseok Oh, Sohee Yang, Vladimir Karpukhin, Yi Lu, and Minjoon Seo. 2022. Nonparametric Decoding for Generative Retrieval. In Annual Meeting of the Association for Computational Linguistics. https:\/\/api.semanticscholar.org\/CorpusID:258959550"},{"key":"e_1_3_2_1_36_1","volume-title":"Tim Rockt\u00e4schel, Sebastian Riedel, and Douwe Kiela.","author":"Lewis Patrick","year":"2020","unstructured":"Patrick Lewis, Ethan Perez, Aleksandara Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Kuttler, Mike Lewis, Wen tau Yih, Tim Rockt\u00e4schel, Sebastian Riedel, and Douwe Kiela. 2020. Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. ArXiv, Vol. abs\/2005.11401. https:\/\/api.semanticscholar.org\/CorpusID:218869575"},{"key":"e_1_3_2_1_37_1","volume-title":"2023 a. Learning to Rank in Generative Retrieval. ArXiv","author":"Li Yongqing","unstructured":"Yongqing Li, Nan Yang, Liang Wang, Furu Wei, and Wenjie Li. 2023 a. Learning to Rank in Generative Retrieval. ArXiv, Vol. abs\/2306.15222. https:\/\/api.semanticscholar.org\/CorpusID:259262395"},{"key":"e_1_3_2_1_38_1","volume-title":"Multiview Identifiers Enhanced Generative Retrieval. In Annual Meeting of the Association for Computational Linguistics. https:\/\/api.semanticscholar.org\/CorpusID:258947148","author":"Li Yongqing","year":"2023","unstructured":"Yongqing Li, Nan Yang, Liang Wang, Furu Wei, and Wenjie Li. 2023 b. Multiview Identifiers Enhanced Generative Retrieval. In Annual Meeting of the Association for Computational Linguistics. https:\/\/api.semanticscholar.org\/CorpusID:258947148"},{"key":"e_1_3_2_1_39_1","volume-title":"Lin and Xueguang Ma","author":"Jimmy","year":"2021","unstructured":"Jimmy J. Lin and Xueguang Ma. 2021. A Few Brief Notes on DeepImpact, COIL, and a Conceptual Framework for Information Retrieval Techniques. ArXiv, Vol. abs\/2106.14807. https:\/\/api.semanticscholar.org\/CorpusID:235658149"},{"key":"e_1_3_2_1_40_1","volume-title":"Lin","author":"Lin Sheng-Chieh","year":"2020","unstructured":"Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy J. Lin. 2020. Distilling Dense Representations for Ranking using Tightly-Coupled Teachers. ArXiv, Vol. abs\/2010.11386. https:\/\/api.semanticscholar.org\/CorpusID:225041183"},{"key":"e_1_3_2_1_41_1","volume-title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach. ArXiv","author":"Liu Yinhan","year":"1989","unstructured":"Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. RoBERTa: A Robustly Optimized BERT Pretraining Approach. ArXiv, Vol. abs\/1907.11692. https:\/\/api.semanticscholar.org\/CorpusID:198953378"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2889473"},{"key":"e_1_3_2_1_43_1","volume-title":"DSI: Updating Transformer Memory with New Documents. ArXiv","author":"Mehta Sanket Vaibhav","year":"2022","unstructured":"Sanket Vaibhav Mehta, Jai Gupta, Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Jinfeng Rao, Marc Najork, Emma Strubell, and Donald Metzler. 2022. DSI: Updating Transformer Memory with New Documents. ArXiv, Vol. abs\/2212.09744. https:\/\/api.semanticscholar.org\/CorpusID:254854290"},{"key":"e_1_3_2_1_44_1","volume-title":"Passage Re-ranking with BERT. ArXiv","author":"Nogueira Rodrigo","unstructured":"Rodrigo Nogueira and Kyunghyun Cho. 2019. Passage Re-ranking with BERT. ArXiv, Vol. abs\/1901.04085. https:\/\/api.semanticscholar.org\/CorpusID:58004692"},{"key":"e_1_3_2_1_45_1","unstructured":"Long Ouyang et al. 2022. Training language models to follow instructions with human feedback. ArXiv Vol. abs\/2203.02155. https:\/\/api.semanticscholar.org\/CorpusID:246426909"},{"key":"e_1_3_2_1_46_1","volume-title":"Minimizing FLOPs to Learn Efficient Sparse Representations. ArXiv","author":"Paria Biswajit","unstructured":"Biswajit Paria, Chih-Kuan Yeh, Ning Xu, Barnab\u00e1s P\u00f3czos, Pradeep Ravikumar, and Ian En-Hsu Yen. 2020a. Minimizing FLOPs to Learn Efficient Sparse Representations. ArXiv, Vol. abs\/2004.05665. https:\/\/api.semanticscholar.org\/CorpusID:211107043"},{"key":"e_1_3_2_1_47_1","volume-title":"Minimizing FLOPs to Learn Efficient Sparse Representations. ArXiv","author":"Paria Biswajit","unstructured":"Biswajit Paria, Chih-Kuan Yeh, Ning Xu, Barnab\u00e1s P\u00f3czos, Pradeep Ravikumar, and Ian En-Hsu Yen. 2020b. Minimizing FLOPs to Learn Efficient Sparse Representations. ArXiv, Vol. abs\/2004.05665. https:\/\/api.semanticscholar.org\/CorpusID:211107043"},{"key":"e_1_3_2_1_48_1","volume-title":"Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:14103653","author":"Ponte Jay M.","unstructured":"Jay M. Ponte and W. Bruce Croft. 1998. A language modeling approach to information retrieval. In Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:14103653"},{"key":"e_1_3_2_1_49_1","volume-title":"Tran","author":"Pradeep Ronak","year":"2023","unstructured":"Ronak Pradeep, Kai Hui, Jai Gupta, \u00c1d\u00e1m D\u00e1niel Lelkes, Honglei Zhuang, Jimmy Lin, Donald Metzler, and Vinh Q. Tran. 2023. How Does Generative Retrieval Scale to Millions of Passages? ArXiv, Vol. abs\/2305.11841. https:\/\/api.semanticscholar.org\/CorpusID:258822999"},{"key":"e_1_3_2_1_50_1","volume-title":"Lin","author":"Pradeep Ronak","year":"2021","unstructured":"Ronak Pradeep, Rodrigo Nogueira, and Jimmy J. Lin. 2021. The Expando-Mono-Duo Design Pattern for Text Ranking with Pretrained Sequence-to-Sequence Models. ArXiv, Vol. abs\/2101.05667. https:\/\/api.semanticscholar.org\/CorpusID:231603106"},{"key":"e_1_3_2_1_51_1","volume-title":"North American","author":"Qu Yingqi","year":"1815","unstructured":"Yingqi Qu, Yuchen Ding, Jing Liu, Kai Liu, Ruiyang Ren, Xin Zhao, Daxiang Dong, Hua Wu, and Haifeng Wang. 2020. RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering. In North American Chapter of the Association for Computational Linguistics. https:\/\/api.semanticscholar.org\/CorpusID:231815627"},{"key":"e_1_3_2_1_52_1","article-title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","volume":"21","author":"Raffel Colin","year":"2019","unstructured":"Colin Raffel, Noam M. Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2019. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. J. Mach. Learn. Res., Vol. 21, 140:1--140:67. https:\/\/api.semanticscholar.org\/CorpusID:204838007","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_1_53_1","volume-title":"Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q","author":"Rajput Shashank","year":"2023","unstructured":"Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan H. Keshavan, Trung Hieu Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, and Maheswaran Sathiamoorthy. 2023. Recommender Systems with Generative Retrieval. ArXiv, Vol. abs\/2305.05065. https:\/\/api.semanticscholar.org\/CorpusID:258564854"},{"key":"e_1_3_2_1_54_1","volume-title":"J. Liu, Huaqin Wu, Ji rong Wen, and Haifeng Wang.","author":"Ren Ruiyang","year":"2023","unstructured":"Ruiyang Ren, Wayne Xin Zhao, J. Liu, Huaqin Wu, Ji rong Wen, and Haifeng Wang. 2023. TOME: A Two-stage Approach for Model-based Retrieval. ArXiv, Vol. abs\/2305.11161. https:\/\/api.semanticscholar.org\/CorpusID:258762633"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.5555\/275537.275701"},{"key":"e_1_3_2_1_56_1","volume-title":"Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:16829071","author":"Stephen","unstructured":"Stephen E. Robertson and Steve Walker. 1997. On relevance weights with little relevance information. In Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:16829071"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1561\/1500000019"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591629"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626772.3657783"},{"key":"e_1_3_2_1_60_1","volume-title":"LaMP: When Large Language Models Meet Personalization. arxiv: 2304","author":"Salemi Alireza","year":"2024","unstructured":"Alireza Salemi, Sheshera Mysore, Michael Bendersky, and Hamed Zamani. 2024 b. LaMP: When Large Language Models Meet Personalization. arxiv: 2304.11406 [cs.CL]"},{"key":"e_1_3_2_1_61_1","volume-title":"Hansi Zeng, Julian Killingback, and Hamed Zamani.","author":"Samarinas Chris","year":"2024","unstructured":"Chris Samarinas, Atharva Nijasure Pracha Promthaw, Hansi Zeng, Julian Killingback, and Hamed Zamani. 2024. Simulating Task-Oriented Dialogues with State Transition Graphs and Large Language Models. In arXiv preprint arXiv:2404.14772."},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1108\/eb026526"},{"key":"e_1_3_2_1_63_1","volume-title":"On NMT Search Errors and Model Errors: Cat Got Your Tongue? ArXiv","author":"Stahlberg Felix","year":"2016","unstructured":"Felix Stahlberg and Bill Byrne. 2019. On NMT Search Errors and Model Errors: Cat Got Your Tongue? ArXiv, Vol. abs\/1908.10090. https:\/\/api.semanticscholar.org\/CorpusID:201646223"},{"key":"e_1_3_2_1_64_1","volume-title":"Learning to Tokenize for Generative Retrieval. ArXiv","author":"Sun Weiwei","unstructured":"Weiwei Sun, Lingyong Yan, Zheng Chen, Shuaiqiang Wang, Haichao Zhu, Pengjie Ren, Zhumin Chen, Dawei Yin, M. de Rijke, and Zhaochun Ren. 2023. Learning to Tokenize for Generative Retrieval. ArXiv, Vol. abs\/2304.04171. https:\/\/api.semanticscholar.org\/CorpusID:258048596"},{"key":"e_1_3_2_1_65_1","volume-title":"Le","author":"Sutskever Ilya","year":"2014","unstructured":"Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014. Sequence to Sequence Learning with Neural Networks. ArXiv, Vol. abs\/1409.3215. https:\/\/api.semanticscholar.org\/CorpusID:7961699"},{"key":"e_1_3_2_1_66_1","volume-title":"Transformer Memory as a Differentiable Search Index. ArXiv","author":"Tay Yi","unstructured":"Yi Tay, Vinh Q. Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Gupta, Tal Schuster, William W. Cohen, and Donald Metzler. 2022. Transformer Memory as a Differentiable Search Index. ArXiv, Vol. abs\/2202.06991. https:\/\/api.semanticscholar.org\/CorpusID:246863488"},{"key":"e_1_3_2_1_67_1","first-page":"2579","article-title":"Visualizing Data using t-SNE","volume":"9","author":"van der Maaten Laurens","year":"2008","unstructured":"Laurens van der Maaten and Geoffrey E. Hinton. 2008. Visualizing Data using t-SNE. Journal of Machine Learning Research, Vol. 9, 2579--2605. https:\/\/api.semanticscholar.org\/CorpusID:5855042","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_68_1","volume-title":"Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:237366133","author":"Wang Shuai","unstructured":"Shuai Wang, Shengyao Zhuang, and G. Zuccon. 2021. BERT-based Dense Retrievers Require Interpolation with BM25 for Effective Passage Retrieval. Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:237366133"},{"key":"e_1_3_2_1_69_1","volume-title":"A Neural Corpus Indexer for Document Retrieval. ArXiv","author":"Wang Yujing","unstructured":"Yujing Wang, Ying Hou, Hong Wang, Ziming Miao, Shibin Wu, Hao Sun, Qi Chen, Yuqing Xia, Chengmin Chi, Guoshuai Zhao, Zheng Liu, Xing Xie, Hao Sun, Weiwei Deng, Qi Zhang, and Mao Yang. 2022. A Neural Corpus Indexer for Document Retrieval. ArXiv, Vol. abs\/2206.02743. https:\/\/api.semanticscholar.org\/CorpusID:249395549"},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3614993"},{"key":"e_1_3_2_1_71_1","unstructured":"Tianxin Wei Bowen Jin Ruirui Li Hansi Zeng Zhengyang Wang Jianhui Sun Qingyu Yin Hanqing Lu Suhang Wang Jingrui He and Xianfeng Tang. 2024. Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond. In The Twelfth International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=khAE1sTMdX"},{"key":"e_1_3_2_1_72_1","volume-title":"Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval. ArXiv","author":"Xiong Lee","year":"2030","unstructured":"Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, and Arnold Overwijk. 2020. Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval. ArXiv, Vol. abs\/2007.00808. https:\/\/api.semanticscholar.org\/CorpusID:220302524"},{"key":"e_1_3_2_1_73_1","volume-title":"Proceedings of the 27th ACM International Conference on Information and Knowledge Management. https:\/\/api.semanticscholar.org\/CorpusID:52229883","author":"Zamani Hamed","unstructured":"Hamed Zamani, Mostafa Dehghani, W. Bruce Croft, Erik G. Learned-Miller, and J. Kamps. 2018. From Neural Re-Ranking to Neural Ranking: Learning a Sparse Representation for Inverted Indexing. Proceedings of the 27th ACM International Conference on Information and Knowledge Management. https:\/\/api.semanticscholar.org\/CorpusID:52229883"},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531722"},{"key":"e_1_3_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591626"},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645477"},{"key":"e_1_3_2_1_77_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531791"},{"key":"e_1_3_2_1_78_1","volume-title":"International Conference on Information and Knowledge Management. https:\/\/api.semanticscholar.org\/CorpusID:1043470","author":"Zhai Cheng Xiang","unstructured":"Cheng Xiang Zhai and John D. Lafferty. 2001. Model-based feedback in the language modeling approach to information retrieval. In International Conference on Information and Knowledge Management. https:\/\/api.semanticscholar.org\/CorpusID:1043470"},{"key":"e_1_3_2_1_79_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462880"},{"key":"e_1_3_2_1_80_1","volume-title":"Proceedings of the ACM Web Conference 2023","author":"Zhang Kai","year":"2022","unstructured":"Kai Zhang, Chongyang Tao, Tao Shen, Can Xu, Xiubo Geng, Binxing Jiao, and Daxin Jiang. 2022. LED: Lexicon-Enlightened Dense Retriever for Large-Scale Retrieval. Proceedings of the ACM Web Conference 2023. https:\/\/api.semanticscholar.org\/CorpusID:251903309"},{"key":"e_1_3_2_1_81_1","volume-title":"Term-Sets Can Be Strong Document Identifiers For Auto-Regressive Search Engines. ArXiv","author":"Zhang Peitian","unstructured":"Peitian Zhang, Zheng Liu, Yujia Zhou, Zhicheng Dou, and Zhao Cao. 2023. Term-Sets Can Be Strong Document Identifiers For Auto-Regressive Search Engines. ArXiv, Vol. abs\/2305.13859. https:\/\/api.semanticscholar.org\/CorpusID:258841428"},{"key":"e_1_3_2_1_82_1","volume-title":"Beam-Stack Search: Integrating Backtracking with Beam Search. In International Conference on Automated Planning and Scheduling. https:\/\/api.semanticscholar.org\/CorpusID:11314454","author":"Zhou R.","unstructured":"R. Zhou and Eric A. Hansen. 2005. Beam-Stack Search: Integrating Backtracking with Beam Search. In International Conference on Automated Planning and Scheduling. https:\/\/api.semanticscholar.org\/CorpusID:11314454"},{"key":"e_1_3_2_1_83_1","volume-title":"Peitian Zhang, and Ji rong Wen.","author":"Zhou Yujia","year":"2022","unstructured":"Yujia Zhou, Jing Yao, Zhicheng Dou, Ledell Yu Wu, Peitian Zhang, and Ji rong Wen. 2022. Ultron: An Ultimate Retriever on Corpus with a Model-based Indexer. ArXiv, Vol. abs\/2208.09257. https:\/\/api.semanticscholar.org\/CorpusID:251710261"},{"key":"e_1_3_2_1_84_1","volume-title":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:252993059","author":"Zhuang Honglei","year":"2022","unstructured":"Honglei Zhuang, Zhen Qin, Rolf Jagerman, Kai Hui, Ji Ma, Jing Lu, Jianmo Ni, Xuanhui Wang, and Michael Bendersky. 2022a. RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses. Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. https:\/\/api.semanticscholar.org\/CorpusID:252993059"},{"key":"e_1_3_2_1_85_1","volume-title":"Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation. ArXiv","author":"Zhuang Shengyao","unstructured":"Shengyao Zhuang, Houxing Ren, Linjun Shou, Jian Pei, Ming Gong, G. Zuccon, and Daxin Jiang. 2022b. Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation. ArXiv, Vol. abs\/2206.10128. https:\/\/api.semanticscholar.org\/CorpusID:249890267"}],"event":{"name":"SIGIR 2024: The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Washington DC USA","acronym":"SIGIR 2024","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3626772.3657746","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3626772.3657746","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T05:31:14Z","timestamp":1755840674000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3626772.3657746"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,10]]},"references-count":85,"alternative-id":["10.1145\/3626772.3657746","10.1145\/3626772"],"URL":"https:\/\/doi.org\/10.1145\/3626772.3657746","relation":{},"subject":[],"published":{"date-parts":[[2024,7,10]]},"assertion":[{"value":"2024-07-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}