🔗 Who cites «Multimodal Hate and Sentiment Understanding in Low-Resource Text-Embedded Images for Online Safety and Digital Well-being»

12 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «Multimodal Hate and Sentiment Understanding in Low-Resource Text-Embedded Images for Online Safety and Digital Well-being»

1. Findings of the Second Workshop on Challenges in Processing South Asian Languages (CHiPSAL 2026)workshop on Challenges in Processing South Asian LanguagesKengatharaiyer Sarveswaran, Surendrabikram Thapa, Ashwini Vaidya, et al.2026 · 12 citations
2. linus@CHiPSAL 2026: Multimodal Hate Speech and Sentiment Detection in Low-Resource Memes Using Late-Fusion Hybrid Architectureworkshop on Challenges in Processing South Asian LanguagesSunil Regmi, Bipesh Subedi, Saugat Singh, et al.2026 · 2 citations
3. MEME-Fusion@CHiPSAL 2026: Multimodal Ablation Study of Hate Detection and Sentiment Analysis on Nepali Memesworkshop on Challenges in Processing South Asian LanguagesSamir Wagle, Reewaj Khanal, Abiral Adhikari2026 · 2 citations
4. NeuralNoodles@CHiPSAL 2026: Late-Fusion Multimodal Stacking for Nepali Meme Sentiment Classificationworkshop on Challenges in Processing South Asian LanguagesSidratul Muntaha, Sabila Anzum, Arpita Mallik, et al.2026 · 2 citations
5. Team Oryu@CHiPSAL 2026: Integrating Text and Vision Transformers for Multimodal Hate Speech Detection in Memesworkshop on Challenges in Processing South Asian LanguagesNoore Tamanna Orny, Joyeta Barua Moni, Md. Abtahee Kabir, et al.2026 · 2 citations
6. eGrantha.ai@CHiPSAL 2026: Stochastic Image Captioning for Robust Hate Speech Detection in Low-Resource Nepali Memesworkshop on Challenges in Processing South Asian LanguagesAnish Thapaliya2026 · 1 citation

6 more papers of our library cite it; they have no page here yet.

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