Výsledky vyhledávání

The Importance of Being Recurrent for Modeling Hierarchical Structure

Autor: Tran, K., Bisazza, A., Monz, C., Riloff, E., Chiang, D., Hockenmaier, J., Tsujii, J.

Publikováno v: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing : EMNLP 2018: Brussels, Belgium, Oct. 31-Nov. 4
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing : EMNLP 2018
EMNLP

Recent work has shown that recurrent neural networks (RNNs) can implicitly capture and exploit hierarchical information when trained to solve common natural language processing tasks such as language modeling (Linzen et al., 2016) and neural machine

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c89018babd3caa9bd8bdbb7e385d8f6c
https://doi.org/10.18653/v1/D18-1503

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Back-Translation Sampling by Targeting Difficult Words in Neural Machine Translation

Autor: Fadaee, M., Monz, C., Riloff, E., Chiang, D., Hockenmaier, J., Tsujii, J.

Publikováno v: EMNLP
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing : EMNLP 2018: Brussels, Belgium, Oct. 31-Nov. 4, 436-446
STARTPAGE=436;ENDPAGE=446;TITLE=Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing : EMNLP 2018

Neural Machine Translation has achieved state-of-the-art performance for several language pairs using a combination of parallel and synthetic data. Synthetic data is often generated by back-translating sentences randomly sampled from monolingual data

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ecffc22d4ff16f57157681a870c022b2

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BanditSum: Extractive Summarization as a Contextual Bandit

Autor: Dong, Y., Shen, Y., Crawford, E., van Hoof, H., Cheung, J.C.K., Riloff, E., Chiang, D., Hockenmaier, J., Tsujii, J.

Publikováno v: EMNLP
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing : EMNLP 2018: Brussels, Belgium, Oct. 31-Nov. 4, 3739-3748
STARTPAGE=3739;ENDPAGE=3748;TITLE=Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing : EMNLP 2018

In this work, we propose a novel method for training neural networks to perform single-document extractive summarization without heuristically-generated extractive labels. We call our approach BanditSum as it treats extractive summarization as a cont

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2f5809ad603014a2715bea2a6939fea
https://hdl.handle.net/11245.1/a11de747-8c4c-442d-a268-d2d1dd43b396

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Memory-based semantic role labeling: Optimizing features, algorithm, and output

Autor: van den Bosch, A., Canisius, S.V.M., Daelemans, W., Hendrickx, I.H.E., Tjong Kim Sang, E.F., Ng, H.T., Riloff, E.

Publikováno v: Proceedings of the Eighth Conference on Computational Natural Language Learning (CONLL-2004), 102-105
STARTPAGE=102;ENDPAGE=105;TITLE=Proceedings of the Eighth Conference on Computational Natural Language Learning (CONLL-2004)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::6ac03791240a76dec934815e87e5d755
https://research.tilburguniversity.edu/en/publications/c4a44fed-b258-46dd-8713-732485cf01ec

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Conference

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Conference

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Conference

Automated dictionary construction for information extraction from text.

Autor: Riloff, E., Lehnert, W.

Publikováno v: Proceedings of 9th IEEE Conference on Artificial Intelligence for Applications; 1993, p93-99, 7p

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Akademický článek

An empirical study of automated dictionary construction for information extraction in three domains.

Autor: Riloff, E¹ (AUTHOR)

Publikováno v: Artificial Intelligence. Aug1996, Vol. 85 Issue 1-2, p101-134. 34p.

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