3 papers · 1 filter
LAET: A Layer-wise Adaptive Ensemble Tuning Framework for Pretrained Language Models
Jawad Ibn Ahad, Muhammad Rafsan Kabir, Robin Krambroeckers +3
Natural Language Processing (NLP) has transformed the financial industry, enabling advancements in areas such as textual analysis, risk management, and forecasting. Large language…
BanglaEmbed: Efficient Sentence Embedding Models for a Low-Resource Language Using Cross-Lingual Distillation Techniques
Muhammad Rafsan Kabir, Md. Mohibur Rahman Nabil, Mohammad Ashrafuzzaman Khan
Sentence-level embedding is essential for various tasks that require understanding natural language. Many studies have explored such embeddings for high-resource languages like Eng…
Beyond Labels: Aligning Large Language Models with Human-like Reasoning
Muhammad Rafsan Kabir, Rafeed Mohammad Sultan, Ihsanul Haque Asif +5
Aligning large language models (LLMs) with a human reasoning approach ensures that LLMs produce morally correct and human-like decisions. Ethical concerns are raised because curren…