Fetching the paper…
Reading the bibliography…
One of the major impediments to the development of new task-oriented dialogue (TOD) systems is the need for human evaluation at multiple stages and iterations of the development process.
Language models are few-shot learners
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. 2020a · 1901
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020b · 1901
Earlier work this paper cites.
Type/token ratios: What do they really tell us?
Brian Richards. 1987 · 1987
Earlier work this paper cites.
How to build user simulators to train RL-based dialog systems
Weiyan Shi, Kun Qian, Xuewei Wang, and Zhou Yu. 2019 · 2000
Earlier work this paper cites.
Convlab-2: An open-source toolkit for building, evaluating, and diagnosing dialogue systems
Qi Zhu, Zheng Zhang, Yan Fang, Xiang Li, Ryuichi Takanobu, Jinchao Li, Baolin Peng, Jianfeng Gao, Xiaoyan Zhu, and Minlie Huang. 2020 · 2002
Earlier work this paper cites.
Soloist: Few-shot task-oriented dialog with a single pretrained auto-regressive model
Baolin Peng, Chunyuan Li, Jinchao Li, Shahin Shayandeh, Lars Liden, and Jianfeng Gao. 2020 · 2005
Earlier work this paper cites.
A survey of statistical user simulation techniques for reinforcement-learning of dialogue management strategies
Jost Schatzmann, Karl Weilhammer, Matt Stuttle, and Steve Young. 2006 · 2006
Earlier work this paper cites.
Testing the performance of spoken dialogue systems by means of an artificially simulated user
Ramón López-Cózar, Zoraida Callejas Carrión, and Michael F. McTear. 2007 · 2007
Earlier work this paper cites.
Syntactic complexity measures for detecting mild cognitive impairment
Brian Roark, Margaret Mitchell, and Kristy Hollingshead. 2007 · 2007
Earlier work this paper cites.
Mtld, vocd-d, and hd-d: A validation study of sophisticated approaches to lexical diversity assessment
Philip M McCarthy and Scott Jarvis. 2010 · 2010
Earlier work this paper cites.
Syntactic dependency distance as sentence complexity measure
Masanori Oya. 2011 · 2011
Earlier work this paper cites.
Effects of text length on lexical diversity measures: Using short texts with less than 200 tokens
Rie Koizumi and Yo In’nami. 2012 · 2012
Earlier work this paper cites.
Can type-token ratio be used to show morphological complexity of languages?
Kimmo Kettunen. 2014 · 2014
Cited alongside, same era.
A diversity-promoting objective function for neural conversation models
Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao, and William B. Dolan. 2016 · 2016
Cited alongside, same era.
Dependency distance differences across interpreting types: implications for cognitive demand
Junying Liang, Yuanyuan Fang, Qianxi Lv, and Haitao Liu. 2017 · 2017
Cited alongside, same era.
Multiwoz - a large-scale multi-domain wizard-of-oz dataset for task-oriented dialogue modelling
Paweł Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng, Iñigo Casanueva, Stefan Ultes, Osman Ramadan, and Milica Gasic. 2018 · 2018
Cited alongside, same era.
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.
Multi-task pre-training for plug-and-play task-oriented dialogue system
Yixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta, Deng Cai, Yi-An Lai, and Yi Zhang. 2021 · 2021
Later among the works it cites.
Gpt-j-6b: A 6 billion parameter autoregressive language model
Ben Wang and Aran Komatsuzaki. 2021 · 2021
Later among the works it cites.
GPT-NeoX-20B: An open-source autoregressive language model
Sidney Black, Stella Biderman, Eric Hallahan, Quentin Anthony, Leo Gao, Laurence Golding, Horace He, Connor Leahy, Kyle McDonell, Jason Phang, Michael Pieler, Usvsn Sai Prashanth, Shivanshu Purohit, Laria Reynolds, Jonathan Tow, Ben Wang, and Samuel Weinbach. 2022 · 2022
Later among the works it cites.
Is multiwoz a solved task? an interactive tod evaluation framework with user simulator
Qinyu Cheng, Linyang Li, Guofeng Quan, Feng Gao, Xiaofeng Mou, and Xipeng Qiu. 2022 · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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, Peter J Liu, et al. 2020 · 2020
Cited alongside, same era.
Towards scalable multi-domain conversational agents: The schema-guided dialogue dataset
Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta, and Pranav Khaitan. 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, Rémi Louf, Morgan Funtowicz, et al. 2020 · 2020
Cited alongside, same era.
Teaching models new apis: Domain-agnostic simulators for task oriented dialogue
Moya Chen, Paul A Crook, and Stephen Roller. 2021 · 2021
Cited alongside, same era.
How to evaluate your dialogue models: A review of approaches
Xinmeng Li, Wansen Wu, Long Qin, and Quanjun Yin. 2021 · 2021
Cited alongside, same era.
Simulated chats for building dialog systems: Learning to generate conversations from instructions
Biswesh Mohapatra, Gaurav Pandey, Danish Contractor, and Sachindra Joshi. 2021 · 2021
Cited alongside, same era.
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Later among the works it cites.
Gentus: Simulating user behaviour and language in task-oriented dialogues with generative transformers
Hsien-Chin Lin, Christian Geishauser, Shutong Feng, Nurul Lubis, Carel van Niekerk, Michael Heck, and Milica Gasic. 2022 · 2022
Later among the works it cites.
Dependency distance measures in assessing l2 writing proficiency
Jinghui Ouyang, Jingyang Jiang, and Haitao Liu. 2022 · 2022
Later among the works it cites.
Bloom: A 176b-parameter open-access multilingual language model
Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, et al. 2022 · 2022
Later among the works it cites.
Alexatm 20b: Few-shot learning using a large-scale multilingual seq2seq model
Saleh Soltan, Shankar Ananthakrishnan, Jack FitzGerald, Rahul Gupta, Wael Hamza, Haidar Khan, Charith Peris, Stephen Rawls, Andy Rosenbaum, Anna Rumshisky, et al. 2022 · 2022
Later among the works it cites.
Metaphorical user simulators for evaluating task-oriented dialogue systems
Weiwei Sun, Shuyu Guo, Shuo Zhang, Pengjie Ren, Zhumin Chen, M. de Rijke, and Zhaochun Ren. 2022 · 2022
Later among the works it cites.
Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou. 2022 · 2022
Later among the works it cites.