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Optimizing accuracy and performance while eliminating hallucinations of open-domain conversational large language models (LLMs) is an open research challenge.
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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Roberta: A robustly optimized bert pretraining approach
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Dialogpt: Large-scale generative pre-training for conversational response generation
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ROUGE: A package for automatic evaluation of summaries
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Open question answering over tables and text
Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Wang, and William W Cohen. 2020a · 2010
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Kgpt: Knowledge-grounded pre-training for data-to-text generation
Wenhu Chen, Yu Su, Xifeng Yan, and William Yang Wang. 2020b · 2010
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Zero-shot visual slot filling as question answering
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Multimodal conversational search and browse
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Learning deep structured semantic models for web search using clickthrough data
Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, and Larry Heck. 2013 · 2013
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Eye gaze for spoken language understanding in multi-modal conversational interactions
Dilek Hakkani-Tür, Malcolm Slaney, Asli Celikyilmaz, and Larry Heck. 2014 · 2014
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Probabilistic enrichment of knowledge graph entities for relation detection in conversational understanding
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Improvements to bm25 and language models examined
Andrew Trotman, Antti Puurula, and Blake Burgess. 2014 · 2014
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Hongzhao Huang, Larry Heck, and Heng Ji. 2015 · 2015
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Compositional semantic parsing on semi-structured tables
Panupong Pasupat and Percy Liang. 2015 · 2015
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Tables as semi-structured knowledge for question answering
Sujay Kumar Jauhar, Peter Turney, and Eduard Hovy. 2016 · 2016
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Search-based neural structured learning for sequential question answering
Mohit Iyyer, Wen-tau Yih, and Ming-Wei Chang. 2017 · 2017
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Learning concepts through conversations in spoken dialogue systems
Robin Jia, Larry Heck, Dilek Hakkani-Tür, and Georgi Nikolov. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Adversarial tableqa: Attention supervision for question answering on tables
Minseok Cho, Reinald Kim Amplayo, Seung-won Hwang, and Jonghyuck Park. 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. 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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Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Dual reader-parser on hybrid textual and tabular evidence for open domain question answering
Alexander Hanbo Li, Patrick Ng, Peng Xu, Henghui Zhu, Zhiguo Wang, and Bing Xiang. 2021 · 2021
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Retrieval augmentation reduces hallucination in conversation
Kurt Shuster, Spencer Poff, Moya Chen, Douwe Kiela, and Jason Weston. 2021 · 2021
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Representations for question answering from documents with tables and text
Vicky Zayats, Kristina Toutanova, and Mari Ostendorf. 2021 · 2021
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Inpars: Data augmentation for information retrieval using large language models
Luiz Bonifacio, Hugo Abonizio, Marzieh Fadaee, and Rodrigo Nogueira. 2022 · 2022
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Large language models are few (1)-shot table reasoners
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ETC: Encoding long and structured inputs in transformers
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HybridQA: A dataset of multi-hop question answering over tabular and textual data
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TaPas: Weakly supervised table parsing via pre-training
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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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Retrieval-augmented generation for knowledge-intensive nlp tasks
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How much knowledge can you pack into the parameters of a language model?
Adam Roberts, Colin Raffel, and Noam Shazeer. 2020 · 2020
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Mixed-modality representation learning and pre-training for joint table-and-text retrieval in openqa
Junjie Huang, Wanjun Zhong, Qian Liu, Ming Gong, Daxin Jiang, and Nan Duan. 2022 · 2022
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Tableformer: Robust transformer modeling for table-text encoding
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Generate rather than retrieve: Large language models are strong context generators
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Contrastive learning of medical visual representations from paired images and text
Yuhao Zhang, Hang Jiang, Yasuhide Miura, Christopher D Manning, and Curtis P Langlotz. 2022 · 2022
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MultiHiertt: Numerical reasoning over multi hierarchical tabular and textual data
Yilun Zhao, Yunxiang Li, Chenying Li, and Rui Zhang. 2022 · 2022
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Inpars-v2: Large language models as efficient dataset generators for information retrieval
Vitor Jeronymo, Luiz Bonifacio, Hugo Abonizio, Marzieh Fadaee, Roberto Lotufo, Jakub Zavrel, and Rodrigo Nogueira. 2023 · 2023
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Commonsense reasoning for conversational ai: A survey of the state of the art
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Replug: Retrieval-augmented black-box language models
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