3 papers
cs.AI2026
Revisiting the Effectiveness of LLM Pruning for Test-Time Scaling
Ocean Monjur, Shahriar Kabir Nahin, Anshuman Chhabra
Large Language Models (LLMs) now exhibit remarkable reasoning capabilities through test-time compute scaling (TTS), with impressive performance across math and coding benchmarks. I…
cs.CL2026
AFRILANGTUTOR: Advancing Language Tutoring and Culture Education in Low-Resource Languages with Large Language Models
Tadesse Destaw Belay, Shahriar Kabir Nahin, Israel Abebe Azime +6
How can language learning systems be developed for languages that lack sufficient training resources? This challenge is increasingly faced by developers across the African continen…
cs.CV2025
Exploring Synergistic Ensemble Learning: Uniting CNNs, MLP-Mixers, and Vision Transformers to Enhance Image Classification
Mk Bashar, Ocean Monjur, Samia Islam +2
In recent years, Convolutional Neural Networks (CNNs), MLP-mixers, and Vision Transformers have risen to prominence as leading neural architectures in image classification. Prior r…