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Large language models (LLMs) have revolutionized the landscape of Natural Language Processing systems, but are computationally expensive.
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. 2020 · 1901
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Well-read students learn better: On the importance of pre-training compact models
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
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The second dialog state tracking challenge
Matthew Henderson, Blaise Thomson, and Jason D. Williams. 2014 · 2014
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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
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Angela Fan, Edouard Grave, and Armand Joulin. 2019 · 2019
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Paul Michel, Omer Levy, and Graham Neubig. 2019 · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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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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Power-bert: Accelerating bert inference via progressive word-vector elimination
Saurabh Goyal, Anamitra Roy Choudhury, Saurabh Raje, Venkatesan Chakaravarthy, Yogish Sabharwal, and Ashish Verma. 2020 · 2020
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End-to-end neural pipeline for goal-oriented dialogue systems using gpt-2
Donghoon Ham, Jeong-Gwan Lee, Youngsoo Jang, and Kee-Eung Kim. 2020 · 2020
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A simple language model for task-oriented dialogue
Ehsan Hosseini-Asl, Bryan McCann, Chien-Sheng Wu, Semih Yavuz, and Richard Socher. 2020 · 2020
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Tinybert: Distilling bert for natural language understanding
Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu. 2020 · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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FastBERT: a self-distilling BERT with adaptive inference time
Weijie Liu, Peng Zhou, Zhiruo Wang, Zhe Zhao, Haotang Deng, and Qi Ju. 2020 · 2020
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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 · 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
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Towards scalable multi-domain conversational agents: The schema-guided dialogue dataset
Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta, and Pranav Khaitan. 2020 · 2020
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Q-bert: Hessian based ultra low precision quantization of bert
Sheng Shen, Zhen Dong, Jiayu Ye, Linjian Ma, Zhewei Yao, Amir Gholami, Michael W Mahoney, and Kurt Keutzer. 2020 · 2020
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Structured pruning of large language models
Ziheng Wang, Jeremy Wohlwend, and Tao Lei. 2020 · 2020
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Improving limited labeled dialogue state tracking with self-supervision
Chien-Sheng Wu, Steven CH Hoi, and Caiming Xiong. 2020 · 2020
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Bert loses patience: Fast and robust inference with early exit
Wangchunshu Zhou, Canwen Xu, Tao Ge, Julian McAuley, Ke Xu, and Furu Wei. 2020 · 2020
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Amazon ec2 update
Jeff Barr. 2019 · 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 · 2021
Efficient edge inference by selective query
Anil Kag, Igor Fedorov, Aditya Gangrade, Paul Whatmough, and Venkatesh Saligrama. 2022 · 2022
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Dialogue summaries as dialogue states (DS2), template-guided summarization for few-shot dialogue state tracking
Jamin Shin, Hangyeol Yu, Hyeongdon Moon, Andrea Madotto, and Juneyoung Park. 2022 · 2022
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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. 2022 · 2022
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Structured pruning learns compact and accurate models
Mengzhou Xia, Zexuan Zhong, and Danqi Chen. 2022 · 2022
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Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I Wang, et al. 2022 · 2022
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Gyuwan Kim and Kyunghyun Cho. 2021 · 2021
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Block pruning for faster transformers
François Lagunas, Ella Charlaix, Victor Sanh, and Alexander M Rush. 2021 · 2021
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Dialogue state tracking with a language model using schema-driven prompting
Chia-Hsuan Lee, Hao Cheng, and Mari Ostendorf. 2021 · 2021
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Aws to offer nvidia’s t4 gpus for ai inferencing
George Leopold. 2019 · 2021
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Zero-shot generalization in dialog state tracking through generative question answering
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Leveraging slot descriptions for zero-shot cross-domain dialogue state tracking
Zhaojiang Lin, Bing Liu, Seungwhan Moon, Paul A Crook, Zhenpeng Zhou, Zhiguang Wang, Zhou Yu, Andrea Madotto, Eunjoon Cho, and Rajen Subba. 2021 · 2021
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MultiWOZ 2.4: A multi-domain task-oriented dialogue dataset with essential annotation corrections to improve state tracking evaluation
Fanghua Ye, Jarana Manotumruksa, and Emine Yilmaz. 2022 · 2022
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Task-optimized adapters for an end-to-end task-oriented dialogue system
Namo Bang, Jeehyun Lee, and Myoung-Wan Koo. 2023 · 2023
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Exploring the benefits of training expert language models over instruction tuning
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Diverse retrieval-augmented in-context learning for dialogue state tracking
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Fly-swat or cannon? cost-effective language model choice via meta-modeling
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