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Nepali meme analysis uses transformers for hate speech and sentiment

By PulseAugur Editorial · [1 sources] ·

Researchers have developed transformer-based models to analyze Nepali memes for hate speech and sentiment. The study focused on text extraction from memes, employing OCR and subsequent analysis with transformer architectures. Experiments showed that a decoder-only model excelled at binary hate speech detection, while a soft voting ensemble approach improved sentiment analysis performance by 15.8% in Macro F1-score. AI

IMPACT Demonstrates advanced NLP techniques for low-resource languages and multimodal content analysis.

RANK_REASON This is a research paper detailing a novel application of transformer models and ensemble learning for text analysis on Nepali memes. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Nepali meme analysis uses transformers for hate speech and sentiment

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This is a research paper detailing a novel application of transformer models and ensemble learning for text analysis on Nepali memes. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Ashish Acharya, Anish Khatiwada, Rohit Khadka, Pragya Aryal ·

    TeamHerald@CHIPSAL 2026: Hate Speech Detection and Sentiment Analysis of Nepali Memes using Transformer-based Architectures and Ensemble Learning

    arXiv:2606.08770v1 Announce Type: cross Abstract: The analysis of internet memes in the Nepali language is complicated by frequent code-mixing and a lack of established baseline resources. While memes inherently combine visual and textual elements, this study focuses on a text-ce…

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