most citedExercise? I thought you said 'Extra Fries': Leveraging Sentence Demarcations and Multi-hop Attention for Meme Affect Analysis

7 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20211 cited

Multimodal Learning using Optimal Transport for Sarcasm and Humor Detection

Shraman Pramanick, Aniket Roy, Vishal M. Patel

Multimodal learning is an emerging yet challenging research area. In this paper, we deal with multimodal sarcasm and humor detection from conversational videos and image-text pairs…

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.MM2021

MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets

Shraman Pramanick, Shivam Sharma, Dimitar Dimitrov +3

Internet memes have become powerful means to transmit political, psychological, and socio-cultural ideas. Although memes are typically humorous, recent days have witnessed an escal…

cs.LG2021

See, Hear, Read: Leveraging Multimodality with Guided Attention for Abstractive Text Summarization

Yash Kumar Atri, Shraman Pramanick, Vikram Goyal +1

In recent years, abstractive text summarization with multimodal inputs has started drawing attention due to its ability to accumulate information from different source modalities a…

cs.CL20217 cited

Exercise? I thought you said 'Extra Fries': Leveraging Sentence Demarcations and Multi-hop Attention for Meme Affect Analysis

Shraman Pramanick, Md Shad Akhtar, Tanmoy Chakraborty

Today's Internet is awash in memes as they are humorous, satirical, or ironic which make people laugh. According to a survey, 33% of social media users in age bracket [13-35] send…