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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 – 6 of 6 1 The Curse of Dense Low-Dimensional Information Retrieval for Large Index Sizes ... 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; ., Iryna; Reimers, Nils. - : Underline Science Inc., 2021 BASE Show details 2 Green NLP panel ... 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; ., Iryna; Arase, Yuki. - : Underline Science Inc., 2021 BASE Show details 3 Investigating label suggestions for opinion mining in German Covid-19 social media ... 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; ., Iryna; Beck, Tilman. - : Underline Science Inc., 2021 BASE Show details 4 Coreference Reasoning in Machine Reading Comprehension ... 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; ., Iryna; Moosavi, Nafise Sadat; Roth, Dan; Wu, Mingzhu. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.448 Abstract: Coreference resolution is essential for natural language understanding and has been long studied in NLP. In recent years, as the format of Question Answering (QA) became a standard for machine reading comprehension (MRC), there have been data collection efforts, e.g., Dasigi et al. (2019), that attempt to evaluate the ability of MRC models to reason about coreference. However, as we show, coreference reasoning in MRC is a greater challenge than earlier thought; MRC datasets do not reflect the natural distribution and, consequently, the challenges of coreference reasoning. Specifically, success on these datasets does not reflect a model's proficiency in coreference reasoning. We propose a methodology for creating MRC datasets that better reflect the challenges of coreference reasoning and use it to create a sample evaluation set. The results on our dataset show that state-of-the-art models still struggle with these phenomena. Furthermore, we ... URL: https://underline.io/lecture/25887-coreference-reasoning-in-machine-reading-comprehension https://dx.doi.org/10.48448/jcqq-1708 BASE Hide details 5 How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models ... 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; ., Iryna; ., Sebastian. - : Underline Science Inc., 2021 BASE Show details 6 Metaphor Generation with Conceptual Mappings ... 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; ., Iryna; Chakrabarty, Tuhin. - : Underline Science Inc., 2021 BASE Show details

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