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20182026
most citedMulti-modal Sarcasm Detection and Humor Classification in Code-mixed Conversations

79 citations · 135 across the 34 of their papers we have counts for

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Showing 2021 · cs.CLShow all

9 papers · 2 filters

cs.CL2021

Nice perfume. How long did you marinate in it? Multimodal Sarcasm Explanation

Poorav Desai, Tanmoy Chakraborty, Md Shad Akhtar

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…

cs.CL2021

Speaker and Time-aware Joint Contextual Learning for Dialogue-act Classification in Counselling Conversations

Ganeshan Malhotra, Abdul Waheed, Aseem Srivastava +2

The onset of the COVID-19 pandemic has brought the mental health of people under risk. Social counselling has gained remarkable significance in this environment. Unlike general goa…

cs.CL2021

Detecting Harmful Memes and Their Targets

Shraman Pramanick, Dimitar Dimitrov, Rituparna Mukherjee +4

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.…

cs.CL2021★ 2 cited

DESYR: Definition and Syntactic Representation Based Claim Detection on the Web

Megha Sundriyal, Parantak Singh, Md Shad Akhtar +2

The formulation of a claim rests at the core of argument mining. To demarcate between a claim and a non-claim is arduous for both humans and machines, owing to latent linguistic va…

cs.CL2021★ 79 cited

Multi-modal Sarcasm Detection and Humor Classification in Code-mixed Conversations

Manjot Bedi, Shivani Kumar, Md Shad Akhtar +1

Sarcasm detection and humor classification are inherently subtle problems, primarily due to their dependence on the contextual and non-verbal information. Furthermore, existing stu…

cs.CL2021

HIT: A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language Representation

Ayan Sengupta, Sourabh Kumar Bhattacharjee, Tanmoy Chakraborty +1

Understanding linguistics and morphology of resource-scarce code-mixed texts remains a key challenge in text processing. Although word embedding comes in handy to support downstrea…