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We present an end-to-end differentiable training method for retrieval-augmented open-domain question answering systems that combine information from multiple retrieved documents when generating answers.
Megatron-lm: Training multi-billion parameter language models using gpu model parallelism
Shoeybi, M., Patwary, M., Puri, R., LeGresley, P., Casper, J., and Catanzaro, B. (2019) · 1909
Earlier work this paper cites.
Maximum likelihood from incomplete data via the em algorithm
Dempster, A., Laird, N., and Rubin, D. (1977) · 1977
Earlier work this paper cites.
Signature verification using a "siamese" time delay neural network
Bromley, J., Guyon, I., LeCun, Y., Säckinger, E., and Shah, R. (1994) · 1994
Earlier work this paper cites.
The probabilistic relevance framework: Bm25 and beyond
Robertson, S. and Zaragoza, H. (2009) · 2009
Earlier work this paper cites.
Learning discriminative projections for text similarity measures
Yih, W.-t., Toutanova, K., Platt, J. C., and Meek, C. (2011) · 2011
Earlier work this paper cites.
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Berant, J., Chou, A., Frostig, R., and Liang, P. (2013) · 2013
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Wang, S., Yu, M., Guo, X., Wang, Z., Klinger, T., Zhang, W., Chang, S., Tesauro, G., Zhou, B., and Jiang, J. (2018) · 2018
Earlier work this paper cites.
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Later among the works it cites.
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Later among the works it cites.
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Qi, P., Zhang, Y., Zhang, Y., Bolton, J., and Manning, C. D. (2020) · 2020
Later among the works it cites.
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Later among the works it cites.
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Later among the works it cites.
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