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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 – 5 of 5 1 AdaTag: Multi-Attribute Value Extraction from Product Profiles with Adaptive Decoding ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Dong, lunadong@amazon.com; Grant, Christan. - : Underline Science Inc., 2021 BASE Show details 2 Adversarial Multitask Learning for Joint Multi-Feature and Multi-Dialect Morphological Modeling ... Zalmout, Nasser; Habash, Nizar. - : arXiv, 2019 Abstract: Morphological tagging is challenging for morphologically rich languages due to the large target space and the need for more training data to minimize model sparsity. Dialectal variants of morphologically rich languages suffer more as they tend to be more noisy and have less resources. In this paper we explore the use of multitask learning and adversarial training to address morphological richness and dialectal variations in the context of full morphological tagging. We use multitask learning for joint morphological modeling for the features within two dialects, and as a knowledge-transfer scheme for cross-dialectal modeling. We use adversarial training to learn dialect invariant features that can help the knowledge-transfer scheme from the high to low-resource variants. We work with two dialectal variants: Modern Standard Arabic (high-resource "dialect") and Egyptian Arabic (low-resource dialect) as a case study. Our models achieve state-of-the-art results for both. Furthermore, adversarial training provides ... : Accepted to ACL 2019 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://arxiv.org/abs/1910.12702 https://dx.doi.org/10.48550/arxiv.1910.12702 BASE Hide details 3 Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging ... Zalmout, Nasser; Habash, Nizar. - : arXiv, 2019 BASE Show details 4 Utilizing Character and Word Embeddings for Text Normalization with Sequence-to-Sequence Models ... Watson, Daniel; Zalmout, Nasser; Habash, Nizar. - : arXiv, 2018 BASE Show details 5 Optimizing Tokenization Choice for Machine Translation across Multiple Target Languages Zalmout Nasser; Habash Nizar In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 257-269 (2017) (2017) BASE Show details

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