Fetching the paper…
Reading the bibliography…
With the enhancement in the field of generative artificial intelligence (AI), contextual question answering has become extremely relevant.
Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 1906
Earlier work this paper cites.
Document ranking with a pretrained sequence-to-sequence model
Rodrigo Nogueira, Zhiying Jiang, and Jimmy Lin. 2020 · 2003
Earlier work this paper cites.
The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al. 2009 · 2009
Earlier work this paper cites.
Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
Earlier work this paper cites.
A survey on truth discovery
Yaliang Li, Jing Gao, Chuishi Meng, Qi Li, Lu Su, Bo Zhao, Wei Fan, and Jiawei Han. 2015 · 2015
Earlier work this paper cites.
Emergent: a novel data-set for stance classification
William Ferreira and Andreas Vlachos. 2016 · 2016
Earlier work this paper cites.
A unified view of gradient-based attribution methods for deep neural networks
Marco Ancona, Enea Ceolini, A. Cengiz Öztireli, and Markus H. Gross. 2017 · 2017
Earlier work this paper cites.
Reading wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
Earlier work this paper cites.
The fake news challenge: Exploring how artificial intelligence technologies could be leveraged to combat fake news
Dean Pomerleau and Delip Rao. 2017 · 2017
Earlier work this paper cites.
The fact extraction and verification (FEVER) shared task
James Thorne, Andreas Vlachos, Oana Cocarascu, Christos Christodoulopoulos, and Arpit Mittal. 2018 · 2018
Earlier work this paper cites.
Truthful AI: developing and governing AI that does not lie
Owain Evans, Owen Cotton-Barratt, Lukas Finnveden, Adam Bales, Avital Balwit, Peter Wills, Luca Righetti, and William Saunders. 2021 · 2021
Earlier work this paper cites.
Towards multi-modal causability with graph neural networks enabling information fusion for explainable AI
Andreas Holzinger, Bernd Malle, Anna Saranti, and Bastian Pfeifer. 2021 · 2021
Cited alongside, same era.
Large dual encoders are generalizable retrievers
Jianmo Ni, Chen Qu, Jing Lu, Zhuyun Dai, Gustavo Hernández Ábrego, Ji Ma, Vincent Y Zhao, Yi Luan, Keith B Hall, Ming-Wei Chang, et al. 2021 · 2021
Cited alongside, same era.
Attributed question answering: Evaluation and modeling for attributed large language models
Bernd Bohnet, Vinh Q Tran, Pat Verga, Roee Aharoni, Daniel Andor, Livio Baldini Soares, Jacob Eisenstein, Kuzman Ganchev, Jonathan Herzig, Kai Hui, et al. 2022 · 2022
Cited alongside, same era.
Evaluating attribution in dialogue systems: The BEGIN benchmark
Nouha Dziri, Hannah Rashkin, Tal Linzen, and David Reitter. 2022 · 2022
Cited alongside, same era.
A survey of large language models attribution
Dongfang Li, Zetian Sun, Xinshuo Hu, Zhenyu Liu, Ziyang Chen, Baotian Hu, Aiguo Wu, and Min Zhang. 2023 · 2023
Later among the works it cites.
Expertqa: Expert-curated questions and attributed answers
Chaitanya Malaviya, Subin Lee, Sihao Chen, Elizabeth Sieber, Mark Yatskar, and Dan Roth. 2023 · 2023
Later among the works it cites.
Measuring attribution in natural language generation models
Hannah Rashkin, Vitaly Nikolaev, Matthew Lamm, Lora Aroyo, Michael Collins, Dipanjan Das, Slav Petrov, Gaurav Singh Tomar, Iulia Turc, and David Reitter. 2023 · 2023
Later among the works it cites.
Semqa: Semi-extractive multi-source question answering
Tal Schuster, Adam D Lelkes, Haitian Sun, Jai Gupta, Jonathan Berant, William W Cohen, and Donald Metzler. 2023 · 2023
Later among the works it cites.
Roformer: Enhanced transformer with rotary position embedding
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick S. H. Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, and Sebastian Riedel. 2022 · 2022
Cited alongside, same era.
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 · 2022
Cited alongside, same era.
The Chicago guide to fact-checking
Brooke Borel. 2023 · 2023
Cited alongside, same era.
Citation: A key to building responsible and accountable large language models
Jie Huang and Kevin Chen-Chuan Chang. 2023 · 2023
Cited alongside, same era.
Retrieving supporting evidence for generative question answering
Siqing Huo, Negar Arabzadeh, and Charles Clarke. 2023 · 2023
Cited alongside, same era.
Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023 · 2023
Cited alongside, same era.
Hagrid: A human-llm collaborative dataset for generative information-seeking with attribution
Ehsan Kamalloo, Aref Jafari, Xinyu Zhang, Nandan Thakur, and Jimmy Lin. 2023 · 2023
Cited alongside, same era.
Rarr: Researching and revising what language models say, using language models
Luyu Gao, Zhuyun Dai, Panupong Pasupat, Anthony Chen, Arun Tejasvi Chaganty, Yicheng Fan, Vincent Zhao, Ni Lao, Hongrae Lee, Da-Cheng Juan, et al. 2023a
Cited in the paper.
Jianlin Su, Murtadha Ahmed, Yu Lu, Shengfeng Pan, Wen Bo, and Yunfeng Liu. 2023 · 2023
Later among the works it cites.
Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023 · 2023
Later among the works it cites.
" according to…" prompting language models improves quoting from pre-training data
Orion Weller, Marc Marone, Nathaniel Weir, Dawn Lawrie, Daniel Khashabi, and Benjamin Van Durme. 2023 · 2023
Later among the works it cites.
Inference with reference: Lossless acceleration of large language models
Nan Yang, Tao Ge, Liang Wang, Binxing Jiao, Daxin Jiang, Linjun Yang, Rangan Majumder, and Furu Wei. 2023 · 2023
Later among the works it cites.
Retrieving multimodal information for augmented generation: A survey
Ruochen Zhao, Hailin Chen, Weishi Wang, Fangkai Jiao, Do Xuan Long, Chengwei Qin, Bosheng Ding, Xiaobao Guo, Minzhi Li, Xingxuan Li, and Shafiq Joty. 2023 · 2023
Later among the works it cites.
Representation engineering: A top-down approach to ai transparency
Andy Zou, Long Phan, Sarah Chen, James Campbell, Phillip Guo, Richard Ren, Alexander Pan, Xuwang Yin, Mantas Mazeika, Ann-Kathrin Dombrowski, et al. 2023 · 2023
Later among the works it cites.
Yi: Open foundation models by 01. ai
Alex Young, Bei Chen, Chao Li, Chengen Huang, Ge Zhang, Guanwei Zhang, Heng Li, Jiangcheng Zhu, Jianqun Chen, Jing Chang, et al. 2024 · 2024
Closest in time.