7 papers
Beyond Real Weights: Hypercomplex Representations for Stable Quantization
Jawad Ibn Ahad, Maisha Rahman, Amrijit Biswas +5
Multimodal language models (MLLMs) require large parameter capacity to align high-dimensional visual features with linguistic representations, making them computationally heavy and…
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…
Video-Based MPAA Rating Prediction: An Attention-Driven Hybrid Architecture Using Contrastive Learning
Dipta Neogi, Nourash Azmine Chowdhury, Muhammad Rafsan Kabir +1
The rapid growth of visual content consumption across platforms necessitates automated video classification for age-suitability standards like the MPAA rating system (G, PG, PG-13,…
Z-Pruner: Post-Training Pruning of Large Language Models for Efficiency without Retraining
Samiul Basir Bhuiyan, Md. Sazzad Hossain Adib, Mohammed Aman Bhuiyan +4
Large language models (LLMs) have rapidly advanced in recent years, achieving remarkable performance across a wide range of natural language processing tasks. However, this progres…
LegalRAG: A Hybrid RAG System for Multilingual Legal Information Retrieval
Muhammad Rafsan Kabir, Rafeed Mohammad Sultan, Fuad Rahman +4
Natural Language Processing (NLP) and computational linguistic techniques are increasingly being applied across various domains, yet their use in legal and regulatory tasks remains…
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…