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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 Page: 1 2 Hits 1 – 20 of 38 1 SyGNS: A Systematic Generalization Testbed Based on Natural Language Semantics ... 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; Inui, Kentaro; Mineshima, Koji. - : Underline Science Inc., 2021 BASE Show details 2 Summarize-then-Answer: Generating Concise Explanations for Multi-hop Reading Comprehension ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Harsh; Balasubramanian, Niranjan. - : Underline Science Inc., 2021 BASE Show details 3 SHAPE: Shifted Absolute Position Embedding for Transformers ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Inui, Kentaro; Kiyono, Shun. - : Underline Science Inc., 2021 BASE Show details 4 Incorporating Residual and Normalization Layers into Analysis of Masked Language Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Inui, Kentaro; Kobayashi, Goro. - : Underline Science Inc., 2021 BASE Show details 5 Pseudo Zero Pronoun Resolution Improves Zero Anaphora Resolution ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Inui, Kentaro; Kiyono, Shun. - : Underline Science Inc., 2021 BASE Show details 6 Exploring Methods for Generating Feedback Comments for Writing Learning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Hanawa, Kazuaki; Inui, Kentaro. - : Underline Science Inc., 2021 BASE Show details 7 Transformer-based Lexically Constrained Headline Generation ... Yamada, Kosuke; Hitomi, Yuta; Tamori, Hideaki. - : arXiv, 2021 BASE Show details 8 Transformer-based Lexically Constrained Headline Generation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Hitomi, Yuta; Inui, Kentaro. - : Underline Science Inc., 2021 BASE Show details 9 Topicalization in Language Models: A Case Study on Japanese ... 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; Abe, Kaori; Fujihara, Riki. - : Underline Science Inc., 2021 BASE Show details 10 Lower Perplexity is Not Always Human-Like ... 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; Asahara, Masayuki; Inui, Kentaro. - : Underline Science Inc., 2021 BASE Show details 11 Lower Perplexity is Not Always Human-Like ... Kuribayashi, Tatsuki; Oseki, Yohei; Ito, Takumi. - : arXiv, 2021 BASE Show details 12 An Empirical Study of Contextual Data Augmentation for Japanese Zero Anaphora Resolution ... Konno, Ryuto; Matsubayashi, Yuichiroh; Kiyono, Shun. - : arXiv, 2020 BASE Show details 13 PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated Contents ... Fujii, Ryo; Mita, Masato; Abe, Kaori. - : arXiv, 2020 BASE Show details 14 Seeing the world through text: Evaluating image descriptions for commonsense reasoning in machine reading comprehension ... The 28th International Conference on Computational Linguistics 2020; Galvan-Sosa, Diana; Inui, Kentaro. - : Underline Science Inc., 2020 BASE Show details 15 Language Models as an Alternative Evaluator of Word Order Hypotheses: A Case Study in Japanese ... Kuribayashi, Tatsuki; Ito, Takumi; Suzuki, Jun; Inui, Kentaro. - : arXiv, 2020 Abstract: We examine a methodology using neural language models (LMs) for analyzing the word order of language. This LM-based method has the potential to overcome the difficulties existing methods face, such as the propagation of preprocessor errors in count-based methods. In this study, we explore whether the LM-based method is valid for analyzing the word order. As a case study, this study focuses on Japanese due to its complex and flexible word order. To validate the LM-based method, we test (i) parallels between LMs and human word order preference, and (ii) consistency of the results obtained using the LM-based method with previous linguistic studies. Through our experiments, we tentatively conclude that LMs display sufficient word order knowledge for usage as an analysis tool. Finally, using the LM-based method, we demonstrate the relationship between the canonical word order and topicalization, which had yet to be analyzed by large-scale experiments. ... : Accepted by ACL2020 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2005.00842 https://dx.doi.org/10.48550/arxiv.2005.00842 BASE Hide details 16 Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction ... Kaneko, Masahiro; Mita, Masato; Kiyono, Shun. - : arXiv, 2020 BASE Show details 17 Attention is Not Only a Weight: Analyzing Transformers with Vector Norms ... Kobayashi, Goro; Kuribayashi, Tatsuki; Yokoi, Sho. - : arXiv, 2020 BASE Show details 18 Filtering Noisy Dialogue Corpora by Connectivity and Content Relatedness ... Akama, Reina; Yokoi, Sho; Suzuki, Jun. - : arXiv, 2020 BASE Show details 19 Modeling Event Salience in Narratives via Barthes' Cardinal Functions ... The 28th International Conference on Computational Linguistics 2020; Inoue, Naoya; Inui, Kentaro. - : Underline Science Inc., 2020 BASE Show details 20 Do Neural Models Learn Systematicity of Monotonicity Inference in Natural Language? ... Yanaka, Hitomi; Mineshima, Koji; Bekki, Daisuke. - : arXiv, 2020 BASE Show details Page: 1 2

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