Fetching the paper…
Reading the bibliography…
Language models (LMs) have revolutionized the way we interact with information, but they often generate nonfactual text, raising concerns about their reliability.
Huggingface’s 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, and Jamie Brew · 1910
Earlier work this paper cites.
A revision of bloom’s taxonomy: An overview
David R Krathwohl · 2002
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
Earlier work this paper cites.
ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
Earlier work this paper cites.
Leveraging linguistic structure for open domain information extraction
Gabor Angeli, Melvin Jose Johnson Premkumar, and Christopher D. Manning · 2015
Earlier work this paper cites.
Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch · 2016
Earlier work this paper cites.
Challenges in data-to-document generation
Sam Wiseman, Stuart Shieber, and Alexander Rush · 2017
Earlier work this paper cites.
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
Earlier work this paper cites.
Shikhar Sharma, Layla El Asri, Hannes Schulz, and Jeremie Zumer · 2017
Earlier work this paper cites.
Faithful to the original: Fact aware neural abstractive summarization
Ziqiang Cao, Furu Wei, Wenjie Li, and Sujian Li · 2018
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Earlier work this paper cites.
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 · 2019
Earlier work this paper cites.
Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, Alexander H Miller, and Sebastian Riedel · 2019
Earlier work this paper cites.
A simple recipe towards reducing hallucination in neural surface realisation
Feng Nie, Jin-Ge Yao, Jinpeng Wang, Rong Pan, and Chin-Yew Lin · 2019
Earlier work this paper cites.
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer · 2019
Earlier work this paper cites.
Assessing the factual accuracy of generated text
Ben Goodrich, Vinay Rao, Peter J. Liu, and Mohammad Saleh · 2019
Earlier work this paper cites.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared 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 M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Earlier work this paper cites.
Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela · 2020
Earlier work this paper cites.
A survey of knowledge-enhanced text generation
Wenhao Yu, Chenguang Zhu, Zaitang Li, Zhiting Hu, Qingyun Wang, Heng Ji, and Meng Jiang · 2020
Earlier work this paper cites.
Kilt: a benchmark for knowledge intensive language tasks
Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vladimir Karpukhin, Jean Maillard, et al · 2020
Earlier work this paper cites.
Realm: Retrieval-augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang · 2020
Earlier work this paper cites.
Evaluating commonsense in pre-trained language models
Xuhui Zhou, Yue Zhang, Leyang Cui, and Dandan Huang · 2020
Earlier work this paper cites.
Multi-fact correction in abstractive text summarization
Yue Dong, Shuohang Wang, Zhe Gan, Yu Cheng, Jackie Chi Kit Cheung, and Jingjing Liu · 2020
Earlier work this paper cites.
Knowledge graph-augmented abstractive summarization with semantic-driven cloze reward
Luyang Huang, Lingfei Wu, and Lu Wang · 2020
Cited alongside, same era.
How can we know what language models know?
Zhengbao Jiang, Frank F Xu, Jun Araki, and Graham Neubig · 2020
Cited alongside, same era.
Reboost: a retrieval-boosted sequence-to-sequence model for neural response generation
Yutao Zhu, Zhicheng Dou, Jian-Yun Nie, and Ji-Rong Wen · 2020
Cited alongside, same era.
Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, and Jason Weston · 2020
Cited alongside, same era.
Scaling language models: Methods, analysis & insights from training gopher
Jack W Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, et al · 2021
Neural path hunter: Reducing hallucination in dialogue systems via path grounding
Nouha Dziri, Andrea Madotto, Osmar Zaiane, and Avishek Joey Bose · 2021
Later among the works it cites.
Factual probing is [mask]: Learning vs. learning to recall
Zexuan Zhong, Dan Friedman, and Danqi Chen · 2021
Later among the works it cites.
Measuring and improving consistency in pretrained language models
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard Hovy, Hinrich Schütze, and Yoav Goldberg · 2021
Later among the works it cites.
Neural machine translation with monolingual translation memory
Deng Cai, Yan Wang, Huayang Li, Wai Lam, and Lemao Liu · 2021
Later among the works it cites.
Bartscore: Evaluating generated text as text generation
Weizhe Yuan, Graham Neubig, and Pengfei Liu · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
WebGPT: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al · 2021
Cited alongside, same era.
The web is your oyster–knowledge-intensive nlp against a very large web corpus
Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Dmytro Okhonko, Samuel Broscheit, Gautier Izacard, Patrick Lewis, Barlas Oğuz, Edouard Grave, Wen-tau Yih, et al · 2021
Cited alongside, same era.
Retrieval augmentation reduces hallucination in conversation
Kurt Shuster, Spencer Poff, Moya Chen, Douwe Kiela, and Jason Weston · 2021
Cited alongside, same era.
Improving language models by retrieving from trillions of tokens
Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George van den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, et al · 2021
Cited alongside, same era.
Leveraging passage retrieval with generative models for open domain question answering
Gautier Izacard and Edouard Grave · 2021
Cited alongside, same era.
FiD-ex: Improving sequence-to-sequence models for extractive rationale generation
Kushal Lakhotia, Bhargavi Paranjape, Asish Ghoshal, Scott Yih, Yashar Mehdad, and Srini Iyer · 2021
Cited alongside, same era.
Inspecting the concept knowledge graph encoded by modern language models
Carlos Aspillaga, Marcelo Mendoza, and Alvaro Soto · 2021
Cited alongside, same era.
Hoon Heo · 2021
Later among the works it cites.
SPLADE: sparse lexical and expansion model for first stage ranking
Thibault Formal, Benjamin Piwowarski, and Stéphane Clinchant · 2021
Later among the works it cites.
Shaden Smith, Mostofa Patwary, Brandon Norick, Patrick LeGresley, Samyam Rajbhandari, Jared Casper, Zhun Liu, Shrimai Prabhumoye, George Zerveas, Vijay Korthikanti, et al · 2022
Later among the works it cites.
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
Later among the works it cites.
Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al · 2022
Later among the works it cites.
Factuality enhanced language models for open-ended text generation
Nayeon Lee, Wei Ping, Peng Xu, Mostofa Patwary, Pascale Fung, Mohammad Shoeybi, and Bryan Catanzaro · 2022
Later among the works it cites.
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
Later among the works it cites.
KG-FiD: Infusing knowledge graph in fusion-in-decoder for open-domain question answering
Donghan Yu, Chenguang Zhu, Yuwei Fang, Wenhao Yu, Shuohang Wang, Yichong Xu, Xiang Ren, Yiming Yang, and Michael Zeng · 2022
Later among the works it cites.
Probing factually grounded content transfer with factual ablation
Peter West, Chris Quirk, Michel Galley, and Yejin Choi · 2022
Later among the works it cites.
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, et al · 2022
Later among the works it cites.
Fid-light: Efficient and effective retrieval-augmented text generation
Sebastian Hofstätter, Jiecao Chen, Karthik Raman, and Hamed Zamani · 2022
Later among the works it cites.
Locating and editing factual knowledge in GPT
Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov · 2022
Later among the works it cites.
Controlling hallucinations at word level in data-to-text generation
Clément Rebuffel, Marco Roberti, Laure Soulier, Geoffrey Scoutheeten, Rossella Cancelliere, and Patrick Gallinari · 2022
Later among the works it cites.
Improving alignment of dialogue agents via targeted human judgements
Amelia Glaese, Nat McAleese, Maja Trębacz, John Aslanides, Vlad Firoiu, Timo Ewalds, Maribeth Rauh, Laura Weidinger, Martin Chadwick, Phoebe Thacker, Lucy Campbell-Gillingham, Jonathan Uesato, Po-Sen Huang, Ramona Comanescu, Fan Yang, Abigail See, Sumanth Dathathri, Rory Greig, Charlie Chen, Doug Fritz, Jaume Sanchez Elias, Richard Green, Soňa Mokrá, Nicholas Fernando, Boxi Wu, Rachel Foley, Susannah Young, Iason Gabriel, William Isaac, John Mellor, Demis Hassabis, Koray Kavukcuoglu, Lisa Anne Hendricks, and Geoffrey Irving · 2022
Later among the works it cites.
Teaching language models to support answers with verified quotes
Jacob Menick, Maja Trebacz, Vladimir Mikulik, John Aslanides, Francis Song, Martin Chadwick, Mia Glaese, Susannah Young, Lucy Campbell-Gillingham, Geoffrey Irving, and Nat McAleese · 2022
Later among the works it cites.
Retromae: Pre-training retrieval-oriented language models via masked auto-encoder
Shitao Xiao, Zheng Liu, Yingxia Shao, and Zhao Cao · 2022
Later among the works it cites.
Hongjing Qian, Yutao Zhu, Zhicheng Dou, Haoqi Gu, Xinyu Zhang, Zheng Liu, Ruofei Lai, Zhao Cao, Jian-Yun Nie, and Ji-Rong Wen · 2023
Closest in time.
Api-bank: A benchmark for tool-augmented llms
Minghao Li, Feifan Song, Bowen Yu, Haiyang Yu, Zhoujun Li, Fei Huang, and Yongbin Li · 2023
Closest in time.