: pretrained domain-specific language model for recognition of Indonesian skill

MythoBERT 1.0: A pre-trained language model for Hindu mythology

The combination of domain adaptation and architectural rigour establishes MythoBERT as a foundational model for computational mythology and opens new avenues in cultural heritage NLP research.

Evaluating the Performance of the No Language Left Behind Encoder for Sentiment Classification Across Multiple Indonesian Regional Languages

This study aims to evaluate the performance of the encoder from the No  Language Left Behind (NLLB) model for sentiment classification tasks  across several Indonesian regional languages. Originally developed for  machine translation, the NLLB model is explored for its ability to generate  contextual text representatio...

MyanmarBERT:Myanmar Pre-trained Language Model using BERT

Advances in Large Language Model

A large language model (LLM) is an AI model (typically a neural network) trained on a vast amount of text for natural language processing tasks, especially language generation. LLMs can typically generate, summarize, translate, and analyze text in many contexts. They are the basis for many modern chatbots, such as Chat...

Kannada-to-English Neural Machine Translation Using an LSTM Encoder-Decoder Architecture

Machine Translation (MT) plays an important role in enabling communication and information access across different languages. However, translating Indian regional languages remains challenging due to limited parallel corpora, morphological richness, flexible word order, and vocabulary variations. Kannada, a widely spok...

Cross-Lingual Transfer for Semantic Role Labeling in Indonesian

This approach addresses the data scarcity problem in Indonesian SRL by leveraging the availability of annotated English-language corpora by leveraging the availability of annotated English-language corpora.