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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 17 of 17 1 MasakhaNER: Named entity recognition for African languages Adelani, David,; Abbott, Jade; Neubig, Graham... In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03350962 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2021, ⟨10.1162/tacl⟩ (2021) BASE Show details 2 Evaluating the Morphosyntactic Well-formedness of Generated Texts ... Pratapa, Adithya; Anastasopoulos, Antonios; Rijhwani, Shruti. - : arXiv, 2021 BASE Show details 3 Explorations in Transfer Learning for OCR Post-Correction ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Neubig, Graham; Rijhwani, Shruti. - : Underline Science Inc., 2021 BASE Show details 4 Evaluating the Morphosyntactic Well-formedness of Generated Texts ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Anastasopoulos, Antonios; Chaudhary, Aditi. - : Underline Science Inc., 2021 BASE Show details 5 Lexically Aware Semi-Supervised Learning for OCR Post-Correction ... Rijhwani, Shruti; Rosenblum, Daisy; Anastasopoulos, Antonios. - : arXiv, 2021 BASE Show details 6 Lexically-Aware Semi-Supervised Learning for OCR Post-Correction ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Anastasopoulos, Antonios; Neubig, Graham. - : Underline Science Inc., 2021 BASE Show details 7 Dependency Induction Through the Lens of Visual Perception ... Su, Ruisi; Rijhwani, Shruti; Zhu, Hao. - : arXiv, 2021 BASE Show details 8 Dependency Induction Through the Lens of Visual Perception ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Hao; Bisk, Yonatan. - : Underline Science Inc., 2021 BASE Show details 9 AlloVera: a multilingual allophone database Mortensen, David,; Li, Xinjian; Littell, Patrick... In: LREC 2020: 12th Language Resources and Evaluation Conference ; https://halshs.archives-ouvertes.fr/halshs-02527046 ; LREC 2020: 12th Language Resources and Evaluation Conference, European Language Resources Association, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/ (2020) BASE Show details 10 AlloVera: A Multilingual Allophone Database ... Mortensen, David R.; Li, Xinjian; Littell, Patrick. - : arXiv, 2020 BASE Show details 11 A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization ... Neubig, Graham; Rijhwani, Shruti; Palmer, Alexis. - : arXiv, 2020 BASE Show details 12 Temporally-Informed Analysis of Named Entity Recognition ... Rijhwani, Shruti; Preoțiuc-Pietro, Daniel. - : Zenodo, 2020 BASE Show details 13 Temporally-Informed Analysis of Named Entity Recognition ... Rijhwani, Shruti; Preoțiuc-Pietro, Daniel. - : Zenodo, 2020 BASE Show details 14 AlloVera: a multilingual allophone database Mortensen, David,; Li, Xinjian; Littell, Patrick... In: LREC 2020: 12th Language Resources and Evaluation Conference ; https://halshs.archives-ouvertes.fr/halshs-02527046 ; LREC 2020: 12th Language Resources and Evaluation Conference, European Language Resources Association, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/ (2020) BASE Show details 15 Improving Candidate Generation for Low-resource Cross-lingual Entity Linking Zhou, Shuyan; Rijhwani, Shruti; Wieting, John... In: Transactions of the Association for Computational Linguistics, Vol 8, Pp 109-124 (2020) (2020) BASE Show details 16 Towards Zero-resource Cross-lingual Entity Linking ... Zhou, Shuyan; Rijhwani, Shruti; Neubig, Graham. - : arXiv, 2019 Abstract: Cross-lingual entity linking (XEL) grounds named entities in a source language to an English Knowledge Base (KB), such as Wikipedia. XEL is challenging for most languages because of limited availability of requisite resources. However, much previous work on XEL has been on simulated settings that actually use significant resources (e.g. source language Wikipedia, bilingual entity maps, multilingual embeddings) that are unavailable in truly low-resource languages. In this work, we first examine the effect of these resource assumptions and quantify how much the availability of these resource affects overall quality of existing XEL systems. Next, we propose three improvements to both entity candidate generation and disambiguation that make better use of the limited data we do have in resource-scarce scenarios. With experiments on four extremely low-resource languages, we show that our model results in gains of 6-23% in end-to-end linking accuracy. ... : Accepted by EMNLP DeepLo workshop 2019 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1909.13180 https://dx.doi.org/10.48550/arxiv.1909.13180 BASE Hide details 17 Zero-shot Neural Transfer for Cross-lingual Entity Linking ... Rijhwani, Shruti; Xie, Jiateng; Neubig, Graham. - : arXiv, 2018 BASE Show details

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