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Ideally, dialogue systems should generate responses that are faithful to the knowledge contained in relevant documents.
CTRL: A conditional transformer language model for controllable generation
Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, Caiming Xiong, and Richard Socher. 2019 · 1909
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Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J. Cohen. 1989 · 1989
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Natural Gradient Works Efficiently in Learning
Shun-ichi Amari. 1998 · 1998
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Revisiting natural gradient for deep networks
Razvan Pascanu and Yoshua Bengio. 2014 · 2014
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al. 2017 · 2017
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Challenges in data-to-document generation
Sam Wiseman, Stuart Shieber, and Alexander Rush. 2017 · 2017
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Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies
Max Grusky, Mor Naaman, and Yoav Artzi. 2018 · 2018
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Polite Dialogue Generation Without Parallel Data
Tong Niu and Mohit Bansal. 2018 · 2018
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Sisyphus, a workflow manager designed for machine translation and automatic speech recognition
Jan-Thorsten Peter, Eugen Beck, and Hermann Ney. 2018 · 2018
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A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
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Wizard of wikipedia: Knowledge-powered conversational agents
Emily Dinan, Stephen Roller, Kurt Shuster, Angela Fan, Michael Auli, and Jason Weston. 2019 · 2019
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Towards zero-shot language modeling
Edoardo Maria Ponti, Ivan Vulić, Ryan Cotterell, Roi Reichart, and Anna Korhonen. 2019 · 2019
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What makes a good conversation? how controllable attributes affect human judgments
Abigail See, Stephen Roller, Douwe Kiela, and Jason Weston. 2019 · 2019
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FEQA: A question answering evaluation framework for faithfulness assessment in abstractive summarization
Esin Durmus, He He, and Mona Diab. 2020 · 2020
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MultiWOZ 2.1: A consolidated multi-domain dialogue dataset with state corrections and state tracking baselines
Mihail Eric, Rahul Goel, Shachi Paul, Abhishek Sethi, Sanchit Agarwal, Shuyang Gao, Adarsh Kumar, Anuj Goyal, Peter Ku, and Dilek Hakkani-Tur. 2020 · 2020
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Improved natural language generation via loss truncation
Daniel Kang and Tatsunori B. Hashimoto. 2020 · 2020
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Beyond domain APIs: Task-oriented conversational modeling with unstructured knowledge access
Seokhwan Kim, Mihail Eric, Karthik Gopalakrishnan, Behnam Hedayatnia, Yang Liu, and Dilek Hakkani-Tur. 2020 · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
ToTTo: A controlled table-to-text generation dataset
Ankur Parikh, Xuezhi Wang, Sebastian Gehrmann, Manaal Faruqui, Bhuwan Dhingra, Diyi Yang, and Dipanjan Das. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
Cited alongside, same era.
On exposure bias, hallucination and domain shift in neural machine translation
Chaojun Wang and Rico Sennrich. 2020 · 2020
Cited alongside, same era.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
On the origin of hallucinations in conversational models: Is it the datasets or the models?
Nouha Dziri, Sivan Milton, Mo Yu, Osmar Zaiane, and Siva Reddy. 2022b · 2022
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Revisiting checkpoint averaging for neural machine translation
Yingbo Gao, Christian Herold, Zijian Yang, and Hermann Ney. 2022 · 2022
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Optimal transport for unsupervised hallucination detection in neural machine translation
Nuno Miguel Guerreiro, Pierre Colombo, Pablo Piantanida, and André F. T. Martins. 2022 · 2022
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Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Yejin Bang, Andrea Madotto, and Pascale Fung. 2022 · 2022
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Fisher sam: Information geometry and sharpness aware minimisation
Minyoung Kim, Da Li, Shell X Hu, and Timothy Hospedales. 2022 · 2022
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Cited alongside, same era.
BERTScore: evaluating text generation with BERT
Tianyi Zhang*, Varsha Kishore*, Felix Wu*, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
Cited alongside, same era.
CaPE: Contrastive parameter ensembling for reducing hallucination in abstractive summarization
Prafulla Kumar Choubey, Alexander R. Fabbri, Jesse Vig, Chien-Sheng Wu, Wenhao Liu, and Nazneen Fatema Rajani. 2021 · 2021
Cited alongside, same era.
Neural path hunter: Reducing hallucination in dialogue systems via path grounding
Nouha Dziri, Andrea Madotto, Osmar Zaïane, and Avishek Joey Bose. 2021 · 2021
Cited alongside, same era.
Parameter-efficient transfer learning with diff pruning
Demi Guo, Alexander Rush, and Yoon Kim. 2021 · 2021
Cited alongside, same era.
Or Honovich, Leshem Choshen, Roee Aharoni, Ella Neeman, Idan Szpektor, and Omri Abend. 2021 · 2021
Cited alongside, same era.
Addressing semantic drift in generative question answering with auxiliary extraction
Chenliang Li, Bin Bi, Ming Yan, Wei Wang, and Songfang Huang. 2021 · 2021
Cited alongside, same era.
DExperts: Decoding-time controlled text generation with experts and anti-experts
Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith, and Yejin Choi. 2021 · 2021
Cited alongside, same era.
QUARK: Controllable text generation with reinforced unlearning
Ximing Lu, Sean Welleck, Jack Hessel, Liwei Jiang, Lianhui Qin, Peter West, Prithviraj Ammanabrolu, and Yejin Choi. 2022 · 2022
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Merging models with fisher-weighted averaging
Michael S Matena and Colin Raffel. 2022 · 2022
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ChatGPT: Optimizing language models for dialogue
OpenAI. 2022 · 2022
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Crossing the conversational chasm: A primer on natural language processing for multilingual task-oriented dialogue systems
Evgeniia Razumovskaia, Goran Glavas, Olga Majewska, Edoardo M Ponti, Anna Korhonen, and Ivan Vulic. 2022 · 2022
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Lamda: Language models for dialog applications
Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Vincent Zhao, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Pranesh Srinivasan, Laichee Man, Kathleen Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Aguera-Arcas, Claire Cui, Marian Croak, Ed Chi, and Quoc Le. 2022 · 2022
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Git re-basin: Merging models modulo permutation symmetries
Samuel Ainsworth, Jonathan Hayase, and Siddhartha Srinivasa. 2023 · 2023
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Characterizing attribution and fluency tradeoffs for retrieval-augmented large language models
Renat Aksitov, Chung-Ching Chang, David Reitter, Siamak Shakeri, and Yun-Hsuan Sung. 2023 · 2023
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Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, Quyet V. Do, Yan Xu, and Pascale Fung. 2023 · 2023
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ChatGPT goes to law school
Jonathan H Choi, Kristin E Hickman, Amy Monahan, and Daniel Schwarcz. 2023 · 2023
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Editing models with task arithmetic
Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi. 2023 · 2023
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The flan collection: Designing data and methods for effective instruction tuning
Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V. Le, Barret Zoph, Jason Wei, and Adam Roberts. 2023 · 2023
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OpenAI. 2023 · 2023
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Jonas Pfeiffer, Sebastian Ruder, Ivan Vulić, and Edoardo Maria Ponti. 2023 · 2023
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Is chatgpt a general-purpose natural language processing task solver?
Chengwei Qin, Aston Zhang, Zhuosheng Zhang, Jiaao Chen, Michihiro Yasunaga, and Diyi Yang. 2023 · 2023
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