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In the rapidly evolving landscape of large language models (LLMs), most research has primarily viewed them as independent individuals, focusing on assessing their capabilities through standardized benchmarks and enhancing their general intelligence.
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Andrei Broder. 2002 · 2002
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Search log analysis: What it is, what’s been done, how to do it
Bernard J Jansen. 2006 · 2006
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Determining the user intent of web search engine queries. In Proceedings of the 16th international conference on World Wide Web . 1149–1150
Bernard J Jansen, Danielle L Booth, and Amanda Spink. 2007 · 2007
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To personalize or not to personalize: modeling queries with variation in user intent. In Proceedings of the 31st annual international ACM SIGIR conference
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User intent in multimedia search: a survey of the state of the art and future challenges
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Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord. 2018 · 2018
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Analyzing and characterizing user intent in information-seeking conversations. In The 41st international acm sigir conference on research & development in information retrieval . 989–992
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User intent, behaviour, and perceived satisfaction in product search. In Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining . 547–555
Ning Su, Jiyin He, Yiqun Liu, Min Zhang, and Shaoping Ma. 2018 · 2018
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Zero-shot user intent detection via capsule neural networks
Congying Xia, Chenwei Zhang, Xiaohui Yan, Yi Chang, and Philip S Yu. 2018 · 2018
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User intent prediction in information-seeking conversations. In Proceedings of the 2019 Conference on Human Information Interaction and Retrieval . 25–33
Chen Qu, Liu Yang, W Bruce Croft, Yongfeng Zhang, Johanne R Trippas, and Minghui Qiu. 2019 · 2019
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Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019 · 2019
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Realtoxicityprompts: Evaluating neural toxic degeneration in language models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A Smith. 2020 · 2020
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2020 · 2020
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Limitations of autoregressive models and their alternatives
Chu-Cheng Lin, Aaron Jaech, Xin Li, Matthew R Gormley, and Jason Eisner. 2020 · 2020
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Machine unlearning. In 2021 IEEE Symposium on Security and Privacy (SP) . IEEE, 141–159
Lucas Bourtoule, Varun Chandrasekaran, Christopher A Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, and Nicolas Papernot. 2021 · 2021
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
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Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al · 2021
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Towards a science of human-ai decision making: a survey of empirical studies
Vivian Lai, Chacha Chen, Q Vera Liao, Alison Smith-Renner, and Chenhao Tan. 2021 · 2021
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Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance
Patrick Mikalef and Manjul Gupta. 2021 · 2021
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Federated evaluation and tuning for on-device personalization: System design & applications
Matthias Paulik, Matt Seigel, Henry Mason, Dominic Telaar, Joris Kluivers, Rogier van Dalen, Chi Wai Lau, Luke Carlson, Filip Granqvist, Chris Vandevelde, et al · 2021
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Winogrande: An adversarial winograd schema challenge at scale
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2021 · 2021
Cited alongside, same era.
How to evaluate trust in AI-assisted decision making? A survey of empirical methodologies
Oleksandra Vereschak, Gilles Bailly, and Baptiste Caramiaux. 2021 · 2021
Cited alongside, same era.
An Empirical Study on How People Perceive AI-generated Music. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management
Hyeshin Chu, Joohee Kim, Seongouk Kim, Hongkyu Lim, Hyunwook Lee, Seungmin Jin, Jongeun Lee, Taehwan Kim, and Sungahn Ko. 2022 · 2022
Cited alongside, same era.
ProcTHOR: Large-Scale Embodied AI Using Procedural Generation
Matt Deitke, Eli VanderBilt, Alvaro Herrasti, Luca Weihs, Kiana Ehsani, Jordi Salvador, Winson Han, Eric Kolve, Aniruddha Kembhavi, and Roozbeh Mottaghi. 2022 · 2022
Cited alongside, same era.
Holistic evaluation of language models
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, et al · 2022
Diversity and language technology: how techno-linguistic bias can cause epistemic injustice
Paula Helm, Gábor Bella, Gertraud Koch, and Fausto Giunchiglia. 2023 · 2023
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Language is not all you need: Aligning perception with language models
Shaohan Huang, Li Dong, Wenhui Wang, Yaru Hao, Saksham Singhal, Shuming Ma, Tengchao Lv, Lei Cui, Owais Khan Mohammed, Qiang Liu, et al · 2023
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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
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A Survey of Reinforcement Learning from Human Feedback
Timo Kaufmann, Paul Weng, Viktor Bengs, and Eyke Hüllermeier. 2023 · 2023
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Cited alongside, same era.
What do Large Language Models Learn beyond Language?
Avinash Madasu and Shashank Srivastava. 2022 · 2022
Cited alongside, same era.
How does the tourism and hospitality industry use artificial intelligence? A review of empirical studies and future research agenda
Mehmet Bahri Saydam, Hasan Evrim Arici, and Mehmet Ali Koseoglu. 2022 · 2022
Cited alongside, same era.
Situating search. In Proceedings of the 2022 Conference on Human Information Interaction and Retrieval . 221–232
Chirag Shah and Emily M Bender. 2022 · 2022
Cited alongside, same era.
Can people experience romantic love for artificial intelligence? An empirical study of intelligent assistants
Xia Song, Bo Xu, and Zhenzhen Zhao. 2022 · 2022
Cited alongside, same era.
Challenging big-bench tasks and whether chain-of-thought can solve them
Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V Le, Ed H Chi, Denny Zhou, et al · 2022
Cited alongside, same era.
GPT-4 Technical Report
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Cited alongside, same era.
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, et al · 2023
Cited alongside, same era.
Bing Chat: The Future of Search Engines?
Dominique Kelly, Yimin Chen, Sarah E Cornwell, Nicole S Delellis, Alex Mayhew, Sodiq Onaolapo, and Victoria L Rubin. 2023 · 2023
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The Alignment Ceiling: Objective Mismatch in Reinforcement Learning from Human Feedback
Nathan Lambert and Roberto Calandra. 2023 · 2023
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Pier Luca Lanzi and Daniele Loiacono. 2023 · 2023
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Alpacaeval: An automatic evaluator of instruction-following models
Xuechen Li, Tianyi Zhang, Yann Dubois, Rohan Taori, Ishaan Gulrajani, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto. 2023 · 2023
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Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models’ Alignment
Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, and Hang Li. 2023 · 2023
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Tool learning with foundation models
Yujia Qin, Shengding Hu, Yankai Lin, Weize Chen, Ning Ding, Ganqu Cui, Zheni Zeng, Yufei Huang, Chaojun Xiao, Chi Han, et al · 2023
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Quantized Transformer Language Model Implementations on Edge Devices
Mohammad Wali Ur Rahman, Murad Mehrab Abrar, Hunter Gibbons Copening, Salim Hariri, Sicong Shao, Pratik Satam, and Soheil Salehi. 2023 · 2023
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Using large language models to generate, validate, and apply user intent taxonomies
Chirag Shah, Ryen W White, Reid Andersen, Georg Buscher, Scott Counts, Sarkar Snigdha Sarathi Das, Ali Montazer, Sathish Manivannan, Jennifer Neville, Xiaochuan Ni, et al · 2023
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Evaluating Large Language Model Creativity from a Literary Perspective
Murray Shanahan and Catherine Clarke. 2023 · 2023
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Ritwik Sinha, Zhao Song, and Tianyi Zhou. 2023 · 2023
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Medical artificial intelligence ethics: A systematic review of empirical studies
Lu Tang, Jinxu Li, and Sophia Fantus. 2023 · 2023
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Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al · 2023
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Llama 2: Open foundation and fine-tuned chat models, 2023
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
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On the robustness of chatgpt: An adversarial and out-of-distribution perspective
Jindong Wang, Xixu Hu, Wenxin Hou, Hao Chen, Runkai Zheng, Yidong Wang, Linyi Yang, Haojun Huang, Wei Ye, Xiubo Geng, et al · 2023
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Plug-and-play document modules for pre-trained models
Chaojun Xiao, Zhengyan Zhang, Xu Han, Chi-Min Chan, Yankai Lin, Zhiyuan Liu, Xiangyang Li, Zhonghua Li, Zhao Cao, and Maosong Sun. 2023b · 2023
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Efficient streaming language models with attention sinks
Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, and Mike Lewis. 2023a · 2023
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A prompt log analysis of text-to-image generation systems. In Proceedings of the ACM Web Conference 2023 . 3892–3902
Yutong Xie, Zhaoying Pan, Jinge Ma, Luo Jie, and Qiaozhu Mei. 2023 · 2023
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Holodeck: Language Guided Generation of 3D Embodied AI Environments
Yue Yang, Fan-Yun Sun, Luca Weihs, Eli VanderBilt, Alvaro Herrasti, Winson Han, Jiajun Wu, Nick Haber, Ranjay Krishna, Lingjie Liu, et al · 2023
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Plug-and-play knowledge injection for pre-trained language models
Zhengyan Zhang, Zhiyuan Zeng, Yankai Lin, Huadong Wang, Deming Ye, Chaojun Xiao, Xu Han, Zhiyuan Liu, Peng Li, Maosong Sun, et al · 2023
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Agieval: A human-centric benchmark for evaluating foundation models
Wanjun Zhong, Ruixiang Cui, Yiduo Guo, Yaobo Liang, Shuai Lu, Yanlin Wang, Amin Saied, Weizhu Chen, and Nan Duan. 2023 · 2023
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