Fetching the paper…
Reading the bibliography…
The task of long-form question answering (LFQA) involves retrieving documents relevant to a given question and using them to generate a paragraph-length answer.
Evalai: Towards better evaluation systems for ai agents
Deshraj Yadav, Rishabh Jain, Harsh Agrawal, Prithvijit Chattopadhyay, Taranjeet Singh, Akash Jain, Shiv Baran Singh, Stefan Lee, and Dhruv Batra. 2019 · 1902
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Sticking to the facts: Confident decoding for faithful data-to-text generation
Ran Tian, Shashi Narayan, Thibault Sellam, and Ankur P Parikh. 2019 · 1910
Earlier work this paper cites.
Measuring nominal scale agreement among many raters
Joseph L Fleiss. 1971 · 1971
Earlier work this paper cites.
The measurement of observer agreement for categorical data
J Richard Landis and Gary G Koch. 1977 · 1977
Earlier work this paper cites.
ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
Evaluation of text generation: A survey
Asli Celikyilmaz, Elizabeth Clark, and Jianfeng Gao. 2020 · 2006
Earlier work this paper cites.
Leveraging passage retrieval with generative models for open domain question answering
Gautier Izacard and Edouard Grave. 2020 · 2007
Earlier work this paper cites.
Question and answer test-train overlap in open-domain question answering datasets
Patrick Lewis, Pontus Stenetorp, and Sebastian Riedel. 2020d · 2008
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, Vassilis Plachouras, Tim Rocktäschel, et al. 2020 · 2009
Earlier work this paper cites.
Hitting the right paraphrases in good time
Stanley Kok and Chris Brockett. 2010 · 2010
Earlier work this paper cites.
Detecting hallucinated content in conditional neural sequence generation
Chunting Zhou, Jiatao Gu, Mona Diab, Paco Guzman, Luke Zettlemoyer, and Marjan Ghazvininejad. 2020 · 2011
Earlier work this paper cites.
Tensorflow: A system for large-scale machine learning
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, et al. 2016 · 2016
Earlier work this paper cites.
First quora dataset release: Question pairs
Shankar Iyer, Nikhil Dandekar, and Kornél Csernai. 2017 · 2017
Earlier work this paper cites.
Challenges in data-to-document generation
Sam Wiseman, Stuart M Shieber, and Alexander M Rush. 2017 · 2017
Earlier work this paper cites.
Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel Bowman, and Noah A Smith. 2018 · 2018
Earlier work this paper cites.
How much reading does reading comprehension require? a critical investigation of popular benchmarks
Divyansh Kaushik and Zachary C Lipton. 2018 · 2018
Earlier work this paper cites.
Generating wikipedia by summarizing long sequences
Peter J Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer. 2018 · 2018
Cited alongside, same era.
Conversational ai: The science behind the alexa prize
Ashwin Ram, Rohit Prasad, Chandra Khatri, Anu Venkatesh, Raefer Gabriel, Qing Liu, Jeff Nunn, Behnam Hedayatnia, Ming Cheng, Ashish Nagar, et al. 2018 · 2018
Cited alongside, same era.
Tensor2tensor for neural machine translation
Ashish Vaswani, Samy Bengio, Eugene Brevdo, Francois Chollet, Aidan N. Gomez, Stephan Gouws, Llion Jones, Łukasz Kaiser, Nal Kalchbrenner, Niki Parmar, Ryan Sepassi, Noam Shazeer, and Jakob Uszkoreit. 2018 · 2018
Cited alongside, same era.
Transfertransfo: A transfer learning approach for neural network based conversational agents
Thomas Wolf, Victor Sanh, Julien Chaumond, and Clement Delangue. 2018 · 2018
Cited alongside, same era.
Texygen: A benchmarking platform for text generation models
A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020 · 2020
Later among the works it cites.
RoFT: A tool for evaluating human detection of machine-generated text
Liam Dugan, Daphne Ippolito, Arun Kirubarajan, and Chris Callison-Burch. 2020 · 2020
Later among the works it cites.
Feqa: A question answering evaluation framework for faithfulness assessment in abstractive summarization
Esin Durmus, He He, and Mona Diab. 2020 · 2020
Later among the works it cites.
Accelerating large-scale inference with anisotropic vector quantization
Ruiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, and Sanjiv Kumar. 2020 · 2020
Later among the works it cites.
REALM: Retrieval-augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020 · 2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yaoming Zhu, Sidi Lu, Lei Zheng, Jiaxian Guo, Weinan Zhang, Jun Wang, and Yong Yu. 2018 · 2018
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Wizard of wikipedia: Knowledge-powered conversational agents
Emily Dinan, Stephen Roller, Kurt Shuster, Angela Fan, Michael Auli, and Jason Weston. 2019 · 2019
Cited alongside, same era.
ELI5: Long form question answering
Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, and Michael Auli. 2019 · 2019
Cited alongside, same era.
Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, et al. 2019 · 2019
Cited alongside, same era.
Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander Miller. 2019 · 2019
Cited alongside, same era.
How to compare summarizers without target length? pitfalls, solutions and re-examination of the neural summarization literature
Simeng Sun, Ori Shapira, Ido Dagan, and Ani Nenkova. 2019 · 2019
Cited alongside, same era.
Later among the works it cites.
The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
Later among the works it cites.
Explain anything like i’m five: A model for open domain long form question answering
Yacine Jernite. 2020 · 2020
Later among the works it cites.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
Later among the works it cites.
Compressive transformers for long-range sequence modelling
Jack W Rae, Anna Potapenko, Siddhant M Jayakumar, Chloe Hillier, and Timothy P Lillicrap. 2020 · 2020
Later among the works it 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. 2020 · 2020
Later among the works it cites.
How much knowledge can you pack into the parameters of a language model?
Adam Roberts, Colin Raffel, and Noam Shazeer. 2020 · 2020
Later among the works it cites.
Efficient content-based sparse attention with routing transformers
Aurko Roy, Mohammad Saffar, Ashish Vaswani, and David Grangier. 2020 · 2020
Later among the works it cites.
Bleurt: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur P Parikh. 2020 · 2020
Later among the works it cites.
Asking and answering questions to evaluate the factual consistency of summaries
Alex Wang, Kyunghyun Cho, and Mike Lewis. 2020 · 2020
Later among the works it cites.
On-the-fly information retrieval augmentation for language models
Hai Wang and David McAllester. 2020 · 2020
Later among the works it cites.
Optimizing the factual correctness of a summary: A study of summarizing radiology reports
Yuhao Zhang, Derek Merck, Emily Bao Tsai, Christopher D Manning, and Curtis P Langlotz. 2020 · 2020
Later among the works it cites.