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In conversational AI research, there's a noticeable trend towards developing models with a larger number of parameters, exemplified by models like ChatGPT.
Plug and play language models: A simple approach to controlled text generation
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Eliza—a computer program for the study of natural language communication between man and machine
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Stacked generalization
David H Wolpert. 1992 · 1992
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Ensemble learning via negative correlation
Yong Liu and Xin Yao. 1999 · 1999
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Towards a human-like open-domain chatbot
Daniel Adiwardana, Minh-Thang Luong, David R. So, Jamie Hall, Noah Fiedel, Romal Thoppilan, Zi Yang, Apoorv Kulshreshtha, Gaurav Nemade, Yifeng Lu, and Quoc V. Le. 2020 · 2001
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Artificial intelligence, values and alignment
Iason Gabriel. 2020 · 2001
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Minimum Bayes-risk decoding for statistical machine translation
Shankar Kumar and William Byrne. 2004 · 2004
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PLATO-2: towards building an open-domain chatbot via curriculum learning
Siqi Bao, Huang He, Fan Wang, Hua Wu, Haifeng Wang, Wenquan Wu, Zhen Guo, Zhibin Liu, and Xinchao Xu. 2020 · 2006
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Combining outputs from multiple machine translation systems
Antti-Veikko Rosti, Necip Fazil Ayan, Bing Xiang, Spyros Matsoukas, Richard Schwartz, and Bonnie Dorr. 2007 · 2007
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman. 2014 · 2014
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Improving neural machine translation models with monolingual data
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2015 · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich. 2015 · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
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A survey on dialogue systems: Recent advances and new frontiers
Hongshen Chen, Xiaorui Liu, Dawei Yin, and Jiliang Tang. 2017 · 2017
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei. 2017 · 2017
Cited alongside, same era.
Ensemble distillation for neural machine translation
Markus Freitag, Yaser Al-Onaizan, and Baskaran Sankaran. 2017 · 2017
Cited alongside, same era.
Ensemble feature selection: homogeneous and heterogeneous approaches
Borja Seijo-Pardo, Iago Porto-Díaz, Verónica Bolón-Canedo, and Amparo Alonso-Betanzos. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
The relative performance of ensemble methods with deep convolutional neural networks for image classification
Cheng Ju, Aurélien Bibaut, and Mark van der Laan. 2018 · 2018
Cited alongside, same era.
BARD: A structured technique for group elicitation of bayesian networks to support analytic reasoning
Erik P. Nyberg, Ann E. Nicholson, Kevin B. Korb, Michael Wybrow, Ingrid Zukerman, Steven Mascaro, Shreshth Thakur, Abraham Oshni Alvandi, Jeff Riley, Ross Pearson, Shane Morris, Matthieu Herrmann, A.K.M. Azad, Fergus Bolger, Ulrike Hahn, and David Lagnado. 2021 · 2021
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Proceedings of the 3rd Workshop on Natural Language Processing for Conversational AI . Association for Computational Linguistics, Online
Alexandros Papangelis, Paweł Budzianowski, Bing Liu, Elnaz Nouri, Abhinav Rastogi, and Yun-Nung Chen, editors. 2021 · 2021
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Recipes for building an open-domain chatbot
Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Eric Michael Smith, Y-Lan Boureau, and Jason Weston. 2021 · 2021
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Grounding in social media: An approach to building a chit-chat dialogue model
Ritvik Choudhary and Daisuke Kawahara. 2022 · 2022
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High quality rather than high model probability: Minimum Bayes risk decoding with neural metrics
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Deep learning-and word embedding-based heterogeneous classifier ensembles for text classification
Zeynep H Kilimci, Selim Akyokus, et al. 2018 · 2018
Cited alongside, same era.
Scalable agent alignment via reward modeling: a research direction
Jan Leike, David Krueger, Tom Everitt, Miljan Martic, Vishal Maini, and Shane Legg. 2018 · 2018
Cited alongside, same era.
Universal adversarial attacks on spoken language assessment systems
Vyas Raina, Mark J.F. Gales, and Kate M. Knill. 2020 · 2020
Cited alongside, same era.
Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano. 2020 · 2020
Cited alongside, same era.
A short survey of pre-trained language models for conversational ai-a new age in nlp
Munazza Zaib, Quan Z. Sheng, and Wei Emma Zhang. 2020 · 2020
Cited alongside, same era.
A general language assistant as a laboratory for alignment
Amanda Askell, Yuntao Bai, Anna Chen, Dawn Drain, Deep Ganguli, Tom Henighan, Andy Jones, Nicholas Joseph, Benjamin Mann, Nova DasSarma, Nelson Elhage, Zac Hatfield-Dodds, Danny Hernandez, Jackson Kernion, Kamal Ndousse, Catherine Olsson, Dario Amodei, Tom B. Brown, Jack Clark, Sam McCandlish, Chris Olah, and Jared Kaplan. 2021 · 2021
Cited alongside, same era.
Summeval: Re-evaluating summarization evaluation
Alexander R. Fabbri, Wojciech Kryściński, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev. 2021 · 2021
Cited alongside, same era.
Markus Freitag, David Grangier, Qijun Tan, and Bowen Liang. 2022 · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
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Deep learning for dialogue systems: Chit-chat and beyond
Rui Yan, Juntao Li, Zhou Yu, et al. 2022 · 2022
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A simple survey of pre-trained language models
Zhenyi Zhu. 2022 · 2022
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Rewarding chatbots for real-world engagement with millions of users
Robert Irvine, Douglas Boubert, Vyas Raina, Adian Liusie, Ziyi Zhu, Vineet Mudupalli, Aliaksei Korshuk, Zongyi Liu, Fritz Cremer, Valentin Assassi, Christie-Carol Beauchamp, Xiaoding Lu, Thomas Rialan, and William Beauchamp. 2023 · 2023
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Llm-blender: Ensembling large language models with pairwise ranking and generative fusion
Dongfu Jiang, Xiang Ren, and Bill Yuchen Lin. 2023 · 2023
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Summary of chatgpt/gpt-4 research and perspective towards the future of large language models
Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, Zihao Wu, Dajiang Zhu, Xiang Li, Ning Qiang, Dingang Shen, Tianming Liu, and Bao Ge. 2023 · 2023
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Adian Liusie, Potsawee Manakul, and Mark J. F. Gales. 2023 · 2023
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Cued at probsum 2023: Hierarchical ensemble of summarization models
Potsawee Manakul, Yassir Fathullah, Adian Liusie, Vyas Raina, Vatsal Raina, and Mark Gales. 2023 · 2023
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Minimum bayes’ risk decoding for system combination of grammatical error correction systems
Vyas Raina and Mark Gales. 2023 · 2023
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