Fetching the paper…
Reading the bibliography…
Narrative-driven recommendation (NDR) presents an information access problem where users solicit recommendations with verbose descriptions of their preferences and context, for example, travelers soliciting recommendations for points of interest while describing their likes/dislikes and travel circumstances.
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
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. 2020 · 1901
Earlier work this paper cites.
Nils Reimers and Iryna Gurevych. 2019 · 1908
Earlier work this paper cites.
Retrieval Evaluation with Incomplete Information. In Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (Sheffield, United Kingdom) (SIGIR ’04) . Association for Computing Machinery, New York, NY, USA, 25–32
Chris Buckley and Ellen M. Voorhees. 2004 · 2004
Earlier work this paper cites.
Personalizing Search via Automated Analysis of Interests and Activities. In Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (Salvador, Brazil) (SIGIR ’05) . Association for Computing Machinery, New York, NY, USA, 449–456
Jaime Teevan, Susan T. Dumais, and Eric Horvitz. 2005 · 2005
Earlier work this paper cites.
Google News Personalization: Scalable Online Collaborative Filtering. In Proceedings of the 16th International Conference on World Wide Web (Banff, Alberta, Canada) (WWW ’07) . Association for Computing Machinery, New York, NY, USA, 271–280
Abhinandan S. Das, Mayur Datar, Ashutosh Garg, and Shyam Rajaram. 2007 · 2007
Earlier work this paper cites.
The Probabilistic Relevance Framework: BM25 and Beyond
Stephen Robertson and Hugo Zaragoza. 2009 · 2009
Earlier work this paper cites.
The YouTube Video Recommendation System. In Proceedings of the Fourth ACM Conference on Recommender Systems (Barcelona, Spain) (RecSys ’10) . Association for Computing Machinery, New York, NY, USA, 293–296
James Davidson, Benjamin Liebald, Junning Liu, Palash Nandy, Taylor Van Vleet, Ullas Gargi, Sujoy Gupta, Yu He, Mike Lambert, Blake Livingston, and Dasarathi Sampath. 2010 · 2010
Earlier work this paper cites.
Query-Driven Context Aware Recommendation. In Proceedings of the 7th ACM Conference on Recommender Systems (Hong Kong, China) (RecSys ’13) . Association for Computing Machinery, New York, NY, USA, 9–16
Negar Hariri, Bamshad Mobasher, and Robin Burke. 2013 · 2013
Earlier work this paper cites.
Personalized Point-of-Interest Recommendation by Mining Users’ Preference Transition. In Proceedings of the 22nd ACM International Conference on Information & Knowledge Management (San Francisco, California, USA) (CIKM ’13) . Association for Computing Machinery, New York, NY, USA, 733–738
Xin Liu, Yong Liu, Karl Aberer, and Chunyan Miao. 2013 · 2013
Earlier work this paper cites.
Overview of the TREC 2016 Contextual Suggestion Track.. In TREC
Seyyed Hadi Hashemi, Jaap Kamps, Julia Kiseleva, Charles LA Clarke, and Ellen M Voorhees. 2016 · 2016
Earlier work this paper cites.
Overview of the CLEF 2016 Social Book Search Lab. In Experimental IR Meets Multilinguality, Multimodality, and Interaction , Norbert Fuhr, Paulo Quaresma, Teresa Gonçalves, Birger Larsen, Krisztian Balog, Craig Macdonald, Linda Cappellato, and Nicola Ferro (Eds.). Springer International Publishing, Cham, 351–370
Marijn Koolen, Toine Bogers, Maria Gäde, Mark Hall, Iris Hendrickx, Hugo Huurdeman, Jaap Kamps, Mette Skov, Suzan Verberne, and David Walsh. 2016 · 2016
Earlier work this paper cites.
Defining and Supporting Narrative-Driven Recommendation. In Proceedings of the Eleventh ACM Conference on Recommender Systems (Como, Italy) (RecSys ’17) . Association for Computing Machinery, New York, NY, USA, 238–242
Toine Bogers and Marijn Koolen. 2017 · 2017
Earlier work this paper cites.
An Experimental Evaluation of Point-of-Interest Recommendation in Location-Based Social Networks
Yiding Liu, Tuan-Anh Nguyen Pham, Gao Cong, and Quan Yuan. 2017 · 2017
Earlier work this paper cites.
“What was this Movie About this Chick?” A Comparative Study of Relevance Aspects in Book and Movie Discovery. In Transforming Digital Worlds: 13th International Conference, iConference 2018, Sheffield, UK, March 25-28, 2018, Proceedings 13 . Springer, 323–334
Toine Bogers, Maria Gäde, Marijn Koolen, Vivien Petras, and Mette Skov. 2018 · 2018
Earlier work this paper cites.
“I’m looking for something like…”: Combining Narratives and Example Items for Narrative-driven Book Recommendation. In Knowledge-aware and Conversational Recommender Systems Workshop . CEUR Workshop Proceedings
Toine Bogers and Marijn Koolen. 2018 · 2018
Earlier work this paper cites.
Item Recommendation on Monotonic Behavior Chains. In Proceedings of the 12th ACM Conference on Recommender Systems (Vancouver, British Columbia, Canada) (RecSys ’18) . Association for Computing Machinery, New York, NY, USA, 86–94
Mengting Wan and Julian McAuley. 2018 · 2018
Earlier work this paper cites.
“Looking for an amazing game I can relax and sink hours into…”: A Study of Relevance Aspects in Video Game Discovery. In Information in Contemporary Society: 14th International Conference, iConference 2019, Washington, DC, USA, March 31–April 3, 2019, Proceedings 14 . Springer, 503–515
Toine Bogers, Maria Gäde, Marijn Koolen, Vivien Petras, and Mette Skov. 2019 · 2019
Earlier work this paper cites.
Evaluating Narrative-Driven Movie Recommendations on Reddit. In Proceedings of the 24th International Conference on Intelligent User Interfaces (Marina del Ray, California) (IUI ’19) . Association for Computing Machinery, New York, NY, USA, 1–11
Lukas Eberhard, Simon Walk, Lisa Posch, and Denis Helic. 2019 · 2019
Cited alongside, same era.
Enhancing Collaborative Filtering with Generative Augmentation. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Anchorage, AK, USA) (KDD ’19) . Association for Computing Machinery, New York, NY, USA, 548–556
Qinyong Wang, Hongzhi Yin, Hao Wang, Quoc Viet Hung Nguyen, Zi Huang, and Lizhen Cui. 2019 · 2019
Cited alongside, same era.
AR-CF: Augmenting Virtual Users and Items in Collaborative Filtering for Addressing Cold-Start Problems. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (Virtual Event, China) (SIGIR ’20) . Association for Computing Machinery, New York, NY, USA, 1251–1260
Dong-Kyu Chae, Jihoo Kim, Duen Horng Chau, and Sang-Wook Kim. 2020 · 2020
Cited alongside, same era.
Precise Zero-Shot Dense Retrieval without Relevance Labels
Luyu Gao, Xueguang Ma, Jimmy Lin, and Jamie Callan. 2022 · 2022
Later among the works it cites.
Unsupervised Dense Information Retrieval with Contrastive Learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2022 · 2022
Later among the works it cites.
Training language models to follow instructions with human feedback. 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., 27730–27744
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
Later among the works it cites.
On Natural Language User Profiles for Transparent and Scrutable Recommendation. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (Madrid, Spain) (SIGIR ’22) . Association for Computing Machinery, New York, NY, USA, 2863–2874
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Latent Linear Critiquing for Conversational Recommender Systems. In The Web Conference
Kai Luo, Scott Sanner, Ga Wu, Hanze Li, and Hojin Yang. 2020 · 2020
Cited alongside, same era.
MPNet: Masked and Permuted Pre-training for Language Understanding. In Advances in Neural Information Processing Systems , Vol. 33
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, and Tie-Yan Liu. 2020 · 2020
Cited alongside, same era.
Jie Zou, Yifan Chen, and Evangelos Kanoulas. 2020 · 2020
Cited alongside, same era.
POINTREC: A Test Collection for Narrative-Driven Point of Interest Recommendation. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (Virtual Event, Canada) (SIGIR ’21) . Association for Computing Machinery, New York, NY, USA, 2478–2484
Jafar Afzali, Aleksander Mark Drzewiecki, and Krisztian Balog. 2021 · 2021
Cited alongside, same era.
Tip of the Tongue Known-Item Retrieval: A Case Study in Movie Identification. In Proceedings of the 6th international ACM SIGIR Conference on Human Information Interaction and Retrieval . ACM
Jaime Arguello, Adam Ferguson, Emery Fine, Bhaskar Mitra, Hamed Zamani, and Fernando Diaz. 2021 · 2021
Cited alongside, same era.
Augmenting the user-item graph with textual similarity models
Federico López, Martin Scholz, Jessica Yung, Marie Pellat, Michael Strube, and Lucas Dixon. 2021 · 2021
Cited alongside, same era.
Zero-shot Neural Passage Retrieval via Domain-targeted Synthetic Question Generation. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume . Association for Computational Linguistics, Online, 1075–1088
Ji Ma, Ivan Korotkov, Yinfei Yang, Keith Hall, and Ryan McDonald. 2021 · 2021
Cited alongside, same era.
CSFCube - A Test Collection of Computer Science Research Articles for Faceted Query by Example. In Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)
Sheshera Mysore, Tim O’Gorman, Andrew McCallum, and Hamed Zamani. 2021 · 2021
Cited alongside, same era.
Starting Conversations with Search Engines - Interfaces That Elicit Natural Language Queries. In Proceedings of the 2021 Conference on Human Information Interaction and Retrieval (Canberra ACT, Australia) (CHIIR ’21) . Association for Computing Machinery, New York, NY, USA, 261–265
Andrea Papenmeier, Dagmar Kern, Daniel Hienert, Alfred Sliwa, Ahmet Aker, and Norbert Fuhr. 2021 · 2021
Cited alongside, same era.
Filip Radlinski, Krisztian Balog, Fernando Diaz, Lucas Dixon, and Ben Wedin. 2022 · 2022
Later among the works it cites.
Improving Passage Retrieval with Zero-Shot Question Generation. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing . Association for Computational Linguistics, Abu Dhabi, United Arab Emirates, 3781–3797
Devendra Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, and Luke Zettlemoyer. 2022 · 2022
Later among the works it cites.
Rethinking Personalized Ranking at Pinterest: An End-to-End Approach. In Proceedings of the 16th ACM Conference on Recommender Systems (Seattle, WA, USA) (RecSys ’22) . Association for Computing Machinery, New York, NY, USA, 502–505
Jiajing Xu, Andrew Zhai, and Charles Rosenberg. 2022 · 2022
Later among the works it cites.
Conversational information seeking
Hamed Zamani, Johanne R Trippas, Jeff Dalton, and Filip Radlinski. 2022 · 2022
Later among the works it cites.
InPars-Light: Cost-Effective Unsupervised Training of Efficient Rankers
Leonid Boytsov, Preksha Patel, Vivek Sourabh, Riddhi Nisar, Sayani Kundu, Ramya Ramanathan, and Eric Nyberg. 2023 · 2023
Closest in time.
Improving Recommendation Fairness via Data Augmentation. In Proceedings of the ACM Web Conference 2023 (Austin, TX, USA) (WWW ’23) . Association for Computing Machinery, New York, NY, USA, 1012–1020
Lei Chen, Le Wu, Kun Zhang, Richang Hong, Defu Lian, Zhiqiang Zhang, Jun Zhou, and Meng Wang. 2023 · 2023
Closest in time.
Promptagator: Few-shot Dense Retrieval From 8 Examples. In The Eleventh International Conference on Learning Representations
Zhuyun Dai, Vincent Y Zhao, Ji Ma, Yi Luan, Jianmo Ni, Jing Lu, Anton Bakalov, Kelvin Guu, Keith Hall, and Ming-Wei Chang. 2023 · 2023
Closest in time.
InPars-v2: Large Language Models as Efficient Dataset Generators for Information Retrieval
Vitor Jeronymo, Luiz Bonifacio, Hugo Abonizio, Marzieh Fadaee, Roberto Lotufo, Jakub Zavrel, and Rodrigo Nogueira. 2023 · 2023
Closest in time.
Megan Leszczynski, Ravi Ganti, Shu Zhang, Krisztian Balog, Filip Radlinski, Fernando Pereira, and Arun Tejasvi Chaganty. 2023 · 2023
Closest in time.
The StatCan Dialogue Dataset: Retrieving Data Tables through Conversations with Genuine Intents. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics . Association for Computational Linguistics, Dubrovnik, Croatia, 2799–2829
Xing Han Lu, Siva Reddy, and Harm de Vries. 2023 · 2023
Closest in time.
Improving Content Retrievability in Search with Controllable Query Generation. In Proceedings of the ACM Web Conference 2023 (Austin, TX, USA) (WWW ’23) . Association for Computing Machinery, New York, NY, USA, 3182–3192
Gustavo Penha, Enrico Palumbo, Maryam Aziz, Alice Wang, and Hugues Bouchard. 2023 · 2023
Closest in time.
UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankers
Jon Saad-Falcon, Omar Khattab, Keshav Santhanam, Radu Florian, Martin Franz, Salim Roukos, Avirup Sil, Md Arafat Sultan, and Christopher Potts. 2023 · 2023
Closest in time.
CAMUS: Attribute-Aware Counterfactual Augmentation for Minority Users in Recommendation. In Proceedings of the ACM Web Conference 2023 (Austin, TX, USA) (WWW ’23) . Association for Computing Machinery, New York, NY, USA, 1396–1404
Yuxin Ying, Fuzhen Zhuang, Yongchun Zhu, Deqing Wang, and Hongwei Zheng. 2023 · 2023
Closest in time.