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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. - : arXiv, 2020 BASE Show 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; Kuribayashi, Tatsuki; Otake, Takaki; Takahashi, Ryo; Yokoi, Sho. - : Underline Science Inc., 2020 Abstract: Events in a narrative differ in salience: some are more important to the story than others. Esti- mating event salience is useful for tasks such as story generation, and as a tool for text analysis in narratology and folkloristics. To compute event salience without any annotations, we adopt Barthes' definition of event salience and propose several unsupervised methods that require only a pre-trained language model. Evaluating the proposed methods on folktales with event salience annotation, we show that the proposed methods outperform baseline methods and find fine-tuning a language model on narrative texts is a key factor in improving the proposed methods. ... Keyword: Computer and Information Science; Natural Language Processing; Neural Network URL: https://dx.doi.org/10.48448/tp8a-3y38 https://underline.io/lecture/6264-modeling-event-salience-in-narratives-via-barthes'-cardinal-functions BASE Hide 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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