Can Large Language Models Detect Personalized Misinformation and Propaganda?
Large language models can detect arguments that would be particularly persuasive to individuals with specific demographics or beliefs, indicating their potential to generate targeted misinformation and propaganda.
IndicLLMSuite: A Blueprint for Indian Language LLMs
인도어 언어 LLM 개발을 위한 청사진 및 자원 소개
RomanSetu: Leveraging Romanization for Multilingual Language Models
RomanSetu proposes using romanized text to enhance the efficiency and performance of Large Language Models for non-English languages.
Magahi Code-mixed Dataset for Sentiment Analysis: MaCmS
Magahi-Hindi-English code-mixed dataset MaCmS introduced for sentiment analysis, highlighting language preferences and challenges in sentiment analysis for low-resourced languages.
Emojinize: Enhancing Text with Emoji Translations
Emojinize introduces a method to translate text into emoji, enhancing communication and comprehension.
INDICVOICES: Building an Inclusive Multilingual Speech Dataset for Indian Languages
Creating a diverse and representative speech dataset for Indian languages to support speech technology development.
NusaBERT: Enhancing Multilingual and Multicultural Understanding in Indonesia
NusaBERT enhances multilingual understanding in Indonesia by incorporating regional languages and dialects, paving the way for future natural language research.
ÌròyìnSpeech: Yorùbá Speech Corpus for TTS and ASR
Increasing high-quality Yorùbá speech data for Text-to-Speech and Automatic Speech Recognition tasks.
Gender Bias Evaluation in Machine Translation Systems
Gender bias persists in commercial machine translation systems, impacting the accuracy of gender translations.
Peacock: Arabic Multimodal Large Language Models and Benchmarks
Peacock introduces Arabic MLLMs for visual reasoning tasks and dialectal potential.
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