Papers by Krishanu Maity
Meme-ingful Analysis: Enhanced Understanding of Cyberbullying in Memes Through Multimodal Explanations (2024.eacl-long)
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| Challenge: | Recent laws like “right to explanations” have spurred research in developing interpretable models . a recent study has shown that multimodal explanations improve performance in generating textual justifications . |
| Approach: | They propose to use visual and textual modalities to explain why a given meme is cyberbullying . they use a Contrastive Language-Image Pretraining approach to generate textual justifications . |
| Outcome: | The proposed model improves performance in visual and textual explanations and identifies the visual evidence supporting a decision. |
ToxVidLM: A Multimodal Framework for Toxicity Detection in Code-Mixed Videos (2024.findings-acl)
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| Challenge: | Using a dataset of 931 videos with 4021 code-mixed Hindi-English utterances, we find that video content with multiple modalities is more accurate and more accurate than textual content. |
| Approach: | They propose to use a dataset to analyze toxic content in video content in non-English languages by leveraging language models. |
| Outcome: | The proposed framework achieves an Accuracy and Weighted F1 score of 94.29% and 94.35% for the first time in its class. |
GenEx: A Commonsense-aware Unified Generative Framework for Explainable Cyberbullying Detection (2023.emnlp-main)
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| Challenge: | a significant gap exists in understanding code-mixed languages and the need for explainability in this context. |
| Approach: | They propose to annotate posts with four labels to identify bullies in code-mixed languages . they propose to use a generative framework to reimagine the multitask problem as a text-to-text generation task. |
| Outcome: | The proposed model outperforms baseline models and state-of-the-art models on the BullyExplain dataset. |