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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 A Comprehensive Understanding of Code-mixed Language Semantics using Hierarchical Transformer ... Sengupta, Ayan; Suresh, Tharun; Akhtar, Md Shad. - : arXiv, 2022 BASE Show details 2 HIT - A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language Representation ... 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; Akhtar, Md Shad; Bhattacharjee, Sourabh. - : Underline Science Inc., 2021 BASE Show details 3 HIT: A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language Representation ... Sengupta, Ayan; Bhattacharjee, Sourabh Kumar; Chakraborty, Tanmoy. - : arXiv, 2021 BASE Show details 4 Nice perfume. How long did you marinate in it? Multimodal Sarcasm Explanation ... Desai, Poorav; Chakraborty, Tanmoy; Akhtar, Md Shad. - : arXiv, 2021 Abstract: Sarcasm is a pervading linguistic phenomenon and highly challenging to explain due to its subjectivity, lack of context and deeply-felt opinion. In the multimodal setup, sarcasm is conveyed through the incongruity between the text and visual entities. Although recent approaches deal with sarcasm as a classification problem, it is unclear why an online post is identified as sarcastic. Without proper explanation, end users may not be able to perceive the underlying sense of irony. In this paper, we propose a novel problem -- Multimodal Sarcasm Explanation (MuSE) -- given a multimodal sarcastic post containing an image and a caption, we aim to generate a natural language explanation to reveal the intended sarcasm. To this end, we develop MORE, a new dataset with explanation of 3510 sarcastic multimodal posts. Each explanation is a natural language (English) sentence describing the hidden irony. We benchmark MORE by employing a multimodal Transformer-based architecture. It incorporates a cross-modal attention in ... : Accepted for publication in AAAI-2022 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2112.04873 https://dx.doi.org/10.48550/arxiv.2112.04873 BASE Hide details 5 Detecting Harmful Memes and Their Targets ... 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; Akhtar, Md Shad; Charaborty, Tanmoy. - : Underline Science Inc., 2021 BASE Show details 6 LESA: Linguistic Encapsulation and Semantic Amalgamation Based Generalised Claim Detection from Online Content ... Gupta, Shreya; Singh, Parantak; Sundriyal, Megha. - : arXiv, 2021 BASE Show details 7 DESYR: Definition and Syntactic Representation Based Claim Detection on the Web ... Sundriyal, Megha; Singh, Parantak; Akhtar, Md Shad. - : arXiv, 2021 BASE Show details 8 Related Tasks can Share! A Multi-task Framework for Affective language ... Deep, Kumar Shikhar; Akhtar, Md Shad; Ekbal, Asif. - : arXiv, 2020 BASE Show details

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