20 citations · 47 across the 14 of their papers we have counts for
5 papers · 1 filter
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…
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.…
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…
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…
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…