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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 – 9 of 9 1 I Wish I Would Have Loved This One, But I Didn't -- A Multilingual Dataset for Counterfactual Detection in Product Reviews ... O'Neill, James; Rozenshtein, Polina; Kiryo, Ryuichi; Kubota, Motoko; Bollegala, Danushka. - : arXiv, 2021 Abstract: Counterfactual statements describe events that did not or cannot take place. We consider the problem of counterfactual detection (CFD) in product reviews. For this purpose, we annotate a multilingual CFD dataset from Amazon product reviews covering counterfactual statements written in English, German, and Japanese languages. The dataset is unique as it contains counterfactuals in multiple languages, covers a new application area of e-commerce reviews, and provides high quality professional annotations. We train CFD models using different text representation methods and classifiers. We find that these models are robust against the selectional biases introduced due to cue phrase-based sentence selection. Moreover, our CFD dataset is compatible with prior datasets and can be merged to learn accurate CFD models. Applying machine translation on English counterfactual examples to create multilingual data performs poorly, demonstrating the language-specificity of this problem, which has been ignored so far. ... : Accepted to EMNLP 2021 ... Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://dx.doi.org/10.48550/arxiv.2104.06893 https://arxiv.org/abs/2104.06893 BASE Hide details 2 Detect and Classify – Joint Span Detection and Classification for Health Outcomes ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Abaho, Micheal; Bollegala, Danushka. - : Underline Science Inc., 2021 BASE Show details 3 Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bollegala, Danushka; Isonuma, Masaru. - : Underline Science Inc., 2021 BASE Show details 4 Fine-Tuning Word Embeddings for Hierarchical Representation of Data Using a Corpus and a Knowledge Base for Various Machine Learning Applications Alsuhaibani, Mohammed; Bollegala, Danushka In: Comput Math Methods Med (2021) BASE Show details 5 RelWalk - A Latent Variable Model Approach to Knowledge Graph Embedding. Bollegala, Danushka; Kawarabayashi, Ken-ichi; Yoshida, Yuichi. - : Association for Computational Linguistics, 2021 BASE Show details 6 Dictionary-based Debiasing of Pre-trained Word Embeddings. Bollegala, Danushka; Kaneko, Masahiro. - : Association for Computational Linguistics, 2021 BASE Show details 7 Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance Sakata, Ichiro; Mori, Junichiro; Bollegala, Danushka. - : Massachusetts Institute of Technology Press, 2021 BASE Show details 8 Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance Bollegala, Danushka; Isonuma, Masaru; Mori, Junichiro. - 2021 BASE Show details 9 Debiasing Pre-trained Contextualised Embeddings. Kaneko, Masahiro; Bollegala, Danushka. - : Association for Computational Linguistics, 2021 BASE Show details

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