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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 BASE Show 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; Dimitrov, Dimitar; Mukherjee, Rituparna; Nakov, Preslav; Pramanick, Shraman; Sharma, Shivam. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.246 Abstract: Among the various modes of communication in social media, the use of Internet memes has emerged as a powerful means to convey political, psychological, and socio-cultural opinions. Although memes are typically humorous in nature, recent days have witnessed a proliferation of harmful memes targeted to abuse various social entities. As most harmful memes are highly satirical and abstruse without appropriate contexts, off-the-shelf multimodal models may not be adequate to understand their underlying semantics. In this work, we propose two novel problem formulations: detecting harmful memes and the social entities that these harmful memes target. To this end, we present HarMeme, the first benchmark dataset, containing 3,544 memes related to COVID-19. Each meme went through a rigorous two-stage annotation process. In the first stage, we labeled a meme as very harmful, partially harmful, or harmless; in the second stage, we further annotated ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://dx.doi.org/10.48448/803b-hv14 https://underline.io/lecture/26337-detecting-harmful-memes-and-their-targets BASE Hide 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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