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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 – 8 of 8 1 Combining Deep Generative Models and Multi-lingual Pretraining for Semi-supervised Document Classification ... Zhu, Yi; Shareghi, Ehsan; Li, Yingzhen. - : arXiv, 2021 BASE Show details 2 It Is Not As Good As You Think! Evaluating Simultaneous Machine Translation on Interpretation Data ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Gholamreza; Arthur, Philip; Cohn, Trevor; Shareghi, Ehsan; Zhao, Jinming. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.537/ Abstract: Most existing simultaneous machine translation (SiMT) systems are trained and evaluated on offline translation corpora. We argue that SiMT systems should be trained and tested on real interpretation data. To illustrate this argument, we propose an interpretation test set and conduct a realistic evaluation of SiMT trained on offline translations. Our results, on our test set along with 3 existing smaller scale language pairs, highlight the difference of up-to 13.83 BLEU score when SiMT models are evaluated on translation vs interpretation data. In the absence of interpretation training data, we propose a translation-to-interpretation (T2I) style transfer method which allows converting existing offline translations into interpretation-style data, leading to up-to 2.8 BLEU improvement. However, the evaluation gap remains notable, calling for constructing large-scale interpretation corpora better suited for evaluating and developing ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing URL: https://dx.doi.org/10.48448/atgp-vb88 https://underline.io/lecture/37602-it-is-not-as-good-as-you-think!-evaluating-simultaneous-machine-translation-on-interpretation-data BASE Hide details 3 A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ... 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; ., Hinrich; Korhonen, Anna. - : Underline Science Inc., 2021 BASE Show details 4 Self-Alignment Pretraining for Biomedical Entity Representations Liu, Fangyu; Shareghi, Ehsan; Meng, Zaiqiao. - : Association for Computational Linguistics, 2021. : Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021 BASE Show details 5 A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ... Zhao, Mengjie; Zhu, Yi; Shareghi, Ehsan. - : arXiv, 2020 BASE Show details 6 Show Some Love to Your n-grams: A Bit of Progress and Stronger n-gram Language Modeling Baselines ... Shareghi, Ehsan; Gerz, Daniela; Vulic, Ivan. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 7 Fast, Small and Exact: Infinite-order Language Modelling with Compressed Suffix Trees ... Shareghi, Ehsan; Petri, Matthias; Haffari, Gholamreza. - : arXiv, 2016 BASE Show details 8 Structured Prediction of Sequences and Trees using Infinite Contexts ... Shareghi, Ehsan; Haffari, Gholamreza; Cohn, Trevor. - : arXiv, 2015 BASE Show details

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